NTIA Report 15-515

Effect of Broadband Radio Service 

Reallocation on 2900–3100 MHz Band 

Marine Radars: Front-end Overload

Robert Achatz

Mark McFarland

Roger Dalke

Geoffrey Sanders

Paul McKenna,

Frank Sanders

Robert Johnk

U.S. DEPARTMENT OF COMMERCE • National Telecommunications and Information Administration

report series
NTIA Report 15-515

Effect of Broadband Radio Service

Reallocation on 2900–3100 MHz Band 

Marine Radars: Front-end Overload

Robert Achatz

Mark McFarland

Roger Dalke

Geoffrey Sanders

Paul McKenna, 

Frank Sanders

Robert Johnk

U.S. DEPARTMENT OF COMMERCE

 April 2015 

DISCLAIMER

Certain commercial equipment and materials are identified in this report to specify adequately 

the technical aspects of the reported results. In no case does such identification imply 

recommendation or endorsement by the National Telecommunications and Information 

Administration, nor does it imply that the material or equipment identified is the best available 

for this purpose.

iii

CONTENTS

Figures........................................................................................................................................... vii

Tables............................................................................................................................................. xi

Acronyms..................................................................................................................................... xiii

Executive Summary.................................................................................................................... xvii

1 Introduction...................................................................................................................................1

1.1 Previous Background Work...................................................................................................4

1.2 Report Organization...............................................................................................................6

2 Front-end Overload.......................................................................................................................7

3 Method ..........................................................................................................................................9

3.1 Effects of Front-End Overload on Pd and Pfa ........................................................................9

3.2 Allowable Interference Power .............................................................................................11

3.3 Separation Distance and Front-End Filter Attenuation........................................................12

4 Mathematical Foundations..........................................................................................................14

4.1 Target RCS Fluctuation .......................................................................................................14

4.2 Interference Measurement Data Processing ........................................................................15

4.2.1 Noise Measurement Data Processing.........................................................................15

4.2.2 Received Signal Data Processing...............................................................................15

4.2.3 Power and Power Ratios.............................................................................................16

5 Front-End Overload Test Fixture................................................................................................18

5.1 Front-end..............................................................................................................................20

5.2 Test Fixture Characterization...............................................................................................22

5.2.1 Front-end Characterization.........................................................................................22

5.2.2 BRS Signal Characterization......................................................................................24

5.3 Instrument Control and Data Processing .............................................................................25

6 Results.........................................................................................................................................26

6.1 Parameters............................................................................................................................26

6.2 IPC .......................................................................................................................................26

6.3 Preliminary Parameter Study...............................................................................................27

6.4 Allowable Interference Power .............................................................................................29

6.5 Aggregate Emissions ...........................................................................................................31

6.6 Front-end Attenuation and Separation Distance..................................................................31

6.7 Comparison of 5%DP to GCP and NEP..............................................................................32

7 Conclusion ..................................................................................................................................34

8 References...................................................................................................................................35

v
9 Acknowledgements.....................................................................................................................38

Appendix A : Effect of Interference on APD and PSD .................................................................39

Appendix B : Uncertainty ..............................................................................................................46

B.1 References...........................................................................................................................52

Appendix C : Schematics and Specifications ................................................................................53

Appendix D : Power Measurement and Calibration......................................................................57

D.1 Sine Wave Power Measurement .........................................................................................57

D.2 Noise Power Measurement .................................................................................................57

D.3 Signal Generator Power Verification..................................................................................57

Appendix E : Characterization Procedures....................................................................................58

E.1 IF Gain and Gain Compression...........................................................................................58

E.2 FE Gain and Gain Compression..........................................................................................59

E.3 System Gain and Gain Compression...................................................................................60

E.4 IF Noise Figure....................................................................................................................60

E.5 System and FE Noise Figure ...............................................................................................61

Appendix F : Characterization Results..........................................................................................62

Appendix G : VSG and VSA SETUP............................................................................................65

G.1 VSG Setup ..........................................................................................................................65

G.2 Creating Interfering Signal for the VSG.............................................................................66

G.3 VSA SETUP .......................................................................................................................66

G.3.1 VSA Setup Parameters..............................................................................................67

G.4 VSA Overload.....................................................................................................................68

G.5 SG and VSG Power Setting ................................................................................................68

Appendix H : Interfering Signal Gain Compression and Noise Enhancement 

Measurement Set Up......................................................................................................................72

vi
FIGURES

Figure 1. Marine radar slotted array antenna (white bar) mounted on motor which 

spins it. .............................................................................................................................................3

Figure 2. BRS base station...............................................................................................................3

Figure 3. Radio spectrum from 2500 to 3700 MHz with current allocations for air 

traffic control (ATC), weather, marine, and various Department of Defense 

(DOD) radar services. ......................................................................................................................4

Figure 4. Physical layout showing a network of BRS base stations contributing to 

the interfering signal power. The interference can cause the radar to not detect the 

target. Antenna pattern attenuation is not represented in this figure. ..............................................6

Figure 5. Interfering power spectral density centered at ffff is within the radar 

front-end bandwidth (BW) (bold outer dashed line). The radar is vulnerable to 

front-end overload............................................................................................................................7

Figure 6. Most of interfering power spectral density centered at ffff is outside of 

the radar front-end bandwidth (BW) (bold outer dashed line). The radar is 

protected from front-end overload...................................................................................................7

Figure 7. General block diagram of BRS transmitters and radar system. TX 

represents the transmitter, TF represents the transmitter filter, TX ANT represents 

the transmitter filter, ANT represents the radar antenna, FEF represents the frontend filter which prevents overload, LNA represents the low-noise amplifier, IFF 

represents the IF filter, and DET represents the threshold detector.................................................8

Figure 8. APD of voltages present at the detector when the interfering signal is 

absent. ............................................................................................................................................10

Figure 9. APD of voltages present at the detector when the interfering signal is 

present............................................................................................................................................10

Figure 10. PPPP over a range of interfering signal powers. ..............................................................11

Figure 11. Flow chart showing sequence of measurement and data processing 

steps................................................................................................................................................12

Figure 12. Radar system block diagram showing key components for analyzing 

front-end overload. FEF represents the front-end filter, LNA represents the lownoise amplifier, MXR represents the mixer, and AMP represents the amplifier...........................18

Figure 13. Front-end overload test fixture block diagram. From left to right are the 

vector signal generator (VSG), band pass filter (BPF), radar signal generator 

(SG), combiner/splitter (C/S), front-end, local oscillator (LO), intermediate 

vii
frequency section (IF), and the test instruments including the vector signal 

analyzer (VSA), spectrum analyzer (SA), and the power meter (PM). .........................................19

Figure 14. Front-end overload test fixture. From top to bottom in the rack are the 

vector signal generator (VSG), vector signal analyzer (VSA), band-pass filter 

(BPF) (small black box), radar signal generator (SG), reference front-end and IF 

section, magnetron front-end assembly, power supplies, local oscillator (LO), and 

power conditioning unit. ................................................................................................................19

Figure 15. Magnetron front-end assembly. Components (from left to right) are 

waveguide terminator, circulator, limiter, and low-noise front-end. The signal and 

interference are applied at the SMA to type-N adaptor on the circulator. The local 

oscillator signal from the signal generator is applied to the SMA connector on top 

of the LNFE. The IF signal is taken from the SMA connector on the side of the 

LNFE..............................................................................................................................................20

Figure 16. Magnetron radar front-end assembly block diagram. CIR represents the 

circulator, LIM represents the limiter, and LNFE represents the low-noise frontend..................................................................................................................................................21

Figure 17. Low-noise front-end block diagram. LNA represents the low-noise 

amplifier, C/S represents the combiner/splitter, circle with a cross represents a 

mixer, and the block with 90o represents the quadrature combiners/splitters................................21

Figure 18. Reference front-end. Components (from top to bottom) are the LNA, 

quadrature splitter, splitter, mixers, and quadrature combiner. The signal and 

interference are applied to the LNA input, the local oscillator signal is applied to 

the splitter, and the IF signal is taken from the quadrature combiner............................................22

Figure 19. Frequency selectivity for circulator, limiter, and their combination. The 

marine radar band extends from 2900-3100 MHz. The radar channel is 60 MHz 

wide and centered at 3050 MHz. The interfering BRS signal was tuned to 2720 

MHz as indicated by the white dashed line. The 2500-2690 MHz band is currently 

used for BRS. The 3500-3650 MHz band is being evaluated........................................................23

Figure 20. Front-end gain compression curves..............................................................................24

Figure 21. Power spectral density of emulated BRS signal...........................................................25

Figure 22. Effect of radar receiver bandwidth and continuous wave (CW) 

interference on reference front-end performance degradation.......................................................28

Figure 23. Effect of pulse integration on reference front-end performance 

degradation.....................................................................................................................................28

Figure 24. Effect of Swerling model and integration on reference front-end 

performance degradation. ..............................................................................................................29

viii
Figure 25. Effect of Swerling model and integration on magnetron front-end 

degradation.....................................................................................................................................30

Figure 26. Reference and magnetron front-end performance degradation for 

Swerling 1, 6 integrations. .............................................................................................................30

Figure 27. Aggregate interference power versus distance for various probabilities 

that the interference power (I) is less than the value on the ordinate (y-axis)...............................31

Figure 28. System gain compression. ............................................................................................33

Figure 29. System noise enhancement...........................................................................................33

Figure A-1. Reference front-end APD at II = -25 dBm..................................................................40

Figure A-2. Reference front-end PSD at II = -25 dBm. .................................................................40

Figure A-3. Reference front-end APD at II = -15 dBm..................................................................41

Figure A-4. Reference front-end PSD at II = -15 dBm. .................................................................41

Figure A-5. Reference front-end APD at II = -12 dBm..................................................................42

Figure A-6. Reference front-end PSD at II = -12 dBm. .................................................................42

Figure A-7. Magnetron front-end assembly APD at II = -25 dBm.................................................43

Figure A-8. Magnetron front-end assembly PSD at II = -25 dBm. ................................................43

Figure A-9. Magnetron front-end assembly APD at II = -10 dBm.................................................44

Figure A-10. Magnetron front-end assembly PSD at II = -10 dBm. ..............................................44

Figure A-11. Magnetron front-end assembly APD at II = -9 dBm.................................................45

Figure A-12. Magnetron front-end assembly PSD at II = -9 dBm. ................................................45

Figure B-1. APD uncertainty in number of points when 106 points are used with a 

10-4 event probability. Vertical lines at 68.3 and 95.5 percent represent one and 

two standard deviations respectively. ............................................................................................48

Figure B-2. APD uncertainty in fractional uncertainty when 106 points are used 

with a 10-4 event probability. Vertical lines at 68.3 and 95.5 percent represent one 

and two standard deviations respectively. .....................................................................................49

Figure B-3. Standard deviation of the mean power estimate as a function of the 

number of Swerling fluctuations....................................................................................................50

Figure B-4. Monte Carlo mean SNR results..................................................................................51

ix
Figure B-5. Monte Carlo mean PPPP results.....................................................................................51

Figure C-1. Front-end overload test fixture with component, cable (Cx), and test 

point (TPx) identifiers. VSG represents the vector signal generator, BPF 

represents the band-pass filter, SG represents the signal generator, C/S represents 

the combiner/splitter, LO represents the local oscillator, VSA represents the 

vector signal analyzer, SA represents the spectrum analyzer, and PM represents 

the power meter..............................................................................................................................53

Figure C-2. Magnetron front-end assembly with test points (TP). CIR represents 

the circulator, LIM represents the limiter, and LNFE represents the low-noise 

front-end.........................................................................................................................................54

Figure C-3. Reference front-end with test points (TP). LNA represents the lownoise amplifier, 90o represents the quadrature combiner/splitter, C/S represents 

the combiner/splitter, and circles with a cross represent a mixer. The mixing stage 

is implemented with two mixers, M1 and M2, to attenuate noise at image 

frequency........................................................................................................................................55

Figure C-4. IF section. LPF represents the low pass filter and BPF represents the 

BPF. ...............................................................................................................................................56

Figure E-1. Gain measurement configurations. SG represents the signal generator 

and SA represents the spectrum analyzer. .....................................................................................60

Figure E-2. Noise figure measurement configurations. ND represents the noise 

diode and PM represents the power meter.....................................................................................61

Figure F-1. IF gain compression....................................................................................................62

Figure F-2. FE gain compression...................................................................................................63

Figure F-3. System gain compression............................................................................................64

Figure G-1. Front-end overload test fixture. VSG represents the vector signal 

generator, BPF represents the band-pass filter, SG represents the signal generator, 

C/S represents the combiner/splitter, LO represents the local oscillator, VSA 

represents the vector signal analyzer, SA represents the spectrum analyzer, and 

PM represents the power meter. LLLLLL, LLLLLLLL, and LLLLLLLL represent various losses. .......................68

Figure H-1. Front-end overload test fixture block diagram. From left to right are 

the vector signal generator (VSG) which creates the BRS signal, band pass filter 

(BPF), power combiner/splitter (C/S), radar signal CW generator (SG), front-end, 

local oscillator (LO), intermediate frequency section (IF), and the test instruments 

including the vector signal analyzer (VSA), spectrum analyzer (SA), and the 

power meter (PM)..........................................................................................................................72

x
TABLES

Table 1. Gain and noise figure measurement results. ....................................................................24

Table 2. Radar and BRS parameters used for analysis. .................................................................26

Table 3. IPC parameters.................................................................................................................26

Table 4. Baseline SNR for a 1.9 degree beam-width antenna at baseline 

performance 0.8 PPPP and 10 − 4 PP PP. PW is pulse width, PRF is pulse repetition 

frequency, BW is IF filter bandwidth, RR is rotation rate, and nnnn is the number of 

pulses integrated.............................................................................................................................27

Table 5. Filter attenuation required for reference front-end at various distances 

when the allowable interference power is -11.5 dBm. Negative attenuation 

corresponds to protection...............................................................................................................32

Table 6. Comparison of various performance metrics...................................................................32

Table A-1. Power levels and probability of detection for reference front-end and 

magnetron front-end assembly.......................................................................................................39

Table C-1. Front-end overload test fixture components. ...............................................................53

Table C-2. Magnetron front-end assembly components................................................................54

Table C-3. Reference front-end components.................................................................................55

Table C-4. IF section components. ................................................................................................56

Table F-1. IF gain. .........................................................................................................................62

Table F-2. FE gain. ........................................................................................................................63

Table F-3. System gain. .................................................................................................................63

Table F-4. IF noise figure. Measured in 20 MHz IF bandwidth....................................................64

Table F-5. System noise figure. Measured in 20 MHz IF bandwidth............................................64

Table F-6. Calculated FE noise figure. ..........................................................................................64

Table G-1. Noise power calculation. .............................................................................................69

Table G-2. Swerling 0 no integration PP calculation..................................................................70

Table G-3. PP calculation.........................................................................................................70

Table G-4. Noise power measured by VSA in 4.63 MHz span calculation. .................................70

xi
Table G-5. Swerling 0 no integration signal power measured by VSA calculation......................70

Table G-6. Mean SNR required without the interfering signal for various Swerling 

types and number of integrations...................................................................................................70

Table H-1. Spectrum analyzer settings. .........................................................................................72

xii
ACRONYMS

3GPP 3rd Generation Partnership Project

ALC Automatic level control

APD Amplitude probability distribution

AWGN Additive white Gaussian noise

BPF Bandpass filter

BRS Broadband radio service

BW Bandwidth

CFAR Constant false alarm rate

CW Continuous wave

dB Decibel

dBi Decibels relative to the gain of an isotropic antenna

dBm Decibels relative to a milliwatt

dBsm Decibels relative to a square meter

dBW Decibels relative to a watt

DOD Department of Defense

DP Degradation point

DUT Device under test

EIRP Effective isotropic radiated power

ETSI European Telecommunications Standards Institute

FDD Frequency division duplex

FDR Frequency dependent rejection

FE Front-end

FEF Front-end filter

FS Free space

GCP Gain compression point

GHz Gigahertz

xiii
GN Gaussian noise

Hz Hertz

IEC International Electrotechnical Committee

IEEE Institute of Electrical and Electronics Engineers

IF Intermediate frequency

INR Interference to noise power ratio

IPC Interference protection criteria

ITM Irregular terrain model

ITS Institute for Telecommunication Sciences

ITU International Telecommunication Union

ITU-R ITU Radiocommunication Sector

kHz kilohertz

km Kilometer

LNA Low-noise amplifier

LNFE Low-noise front-end

LTE Long Term Evolution

MHz Megahertz

MIMO Multiple-input multiple-output

MSC Maritime Safety Committee

NEP Noise enhancement point

nmi Nautical mile

ns Nanosecond

NTIA National Telecommunications and Information Administration

NVWFM Non-volatile waveform memory

OFDM Orthogonal frequency division multiplexing

OFDMA Orthogonal frequency division multiple access

OOB Out-of-band

xiv
PM Power meter

PRF Pulse repetition frequency

PRI Pulse repetition interval

PSD Power spectral density

RCS Radar cross section

RF Radio frequency

RPM Revolutions per minute

SA Spectrum analyzer

SA Spectrum analyzer

SG Signal generator

SINR Signal to interference plus noise ratio

SMA Sub-miniature version A (connector)

SNR Signal to noise ratio

SOLAS Safety of life at sea

STC Sensitivity time control

TDD Time division duplex

UMTS Universal Mobile Telecommunications System

UN United Nations

UN/MSC United Nations Maritime Safety Committee

USCG United States Coast Guard

VSA Vector signal analyzer

VSA Vector signal analyzer

VSG Vector signal generator

WGN White Gaussian noise

WiMAX Worldwide interoperability for microwave access

xv

EXECUTIVE SUMMARY

Spectrum reallocation is often necessary to accommodate new services which can potentially 

increase business productivity and enhance the lives of private citizens. However, reallocating 

services to bands near those used by incumbent services—or, in some cases, to those same 

bands—can cause interference to the incumbent service.

Spectrum reallocation can cause interference in radar systems in a number of ways. A system 

reallocated to a nearby band can introduce unwanted signals into the radar detection bandwidth. 

Also, a system reallocated to a nearby band can overload the radar receiver front-end and cause 

gain compression, increased noise power, and intermodulation in the radar detection bandwidth. 

The U.S. Coast Guard (USCG) asked the National Telecommunications and Information 

Administration Institute for Telecommunication Sciences (NTIA/ITS) to investigate effects of 

reallocation on the 2900–3100 MHz band marine radar service by determining interference 

protection criteria (IPC) and analyzing strategies for mitigating the interference.

Here we investigate the effects of reallocation to accommodate broadband radio services (BRS) 

on the 2900–3100 MHz band marine radar service. The BRS is the next generation of personal 

communications services which will provide wideband Internet communications to mobile users. 

Results of our investigations have been assembled into three reports subtitled “Background,” 

“Unwanted Emissions,” and “Front-end Overload.”

This report describes a methodology for analyzing magnetron radar receiver front-end overload 

caused by signals from an aggregate of broadband radio service (BRS) base stations transmitting 

at frequencies within the radar front-end bandwidth.

The analysis in this report determines how much front-end filter attenuation is needed for various 

separation distances. The attenuation is the difference between the interfering power at the radar 

low-noise front-end (LNFE) and the allowable interference power. 

The interfering power present at the LNFE is determined with a propagation model and a 

methodology for aggregating the signals from a network of base stations. Because of non-linear 

analytic complexity, allowable interference power, IIaa, is determined by probability of detection 

laboratory measurements.

Two front-ends were examined. The first was an off-the-shelf magnetron radar front-end 

assembly with a circulator, limiter, and low-noise front-end. The second was what we refer to as 

a reference front-end consisting of a low-noise front-end constructed from discrete RF 

components. The reference front-end had approximately the same characteristics as the 

magnetron front-end assembly. However, the reference front-end did not have the filtering 

provided by the magnetron front-end assembly circulator and limiter.

The 5% degradation point (5% DP) measurements found IIaa to be -11.5 and -9 dBm for the 

reference front-end and magnetron front-end assembly, respectively. Propagation analysis 

showed that interference powers were less than -23.6 dBm at a 1 km separation distance from the 

closest base station. Consequently, the front-end does not need filter attenuation for distances as 

xvii
close as 400 meters. Distances less than 400 meters were not analyzed due to antenna near field 

effects. Since the magnetron front-end assembly IIaa is greater than the reference front-end’s, this 

result would be true for the magnetron front-end assembly as well.

Gain compression and noise enhancement metrics, which are simpler to measure than the 5% DP 

metric, were also evaluated to determine if they could reliably predict IIaa. We found that only the 

noise enhancement metric predicted it for both front-ends. This result is important since many 

front-end overload studies are based on the gain compression metrics.

The results in this report are encumbered with two caveats. First, the results are for an FDD BRS 

base station signal that occupies one 10 MHz BRS channel. Results need to be adjusted to 

accommodate more channels. Second, these results are based on magnetron radar signal 

processing. Additional analysis is needed to assess the impact to solid state radar receivers 

because their signal processing is very different from that in the magnetron radar receivers. The 

signal processing affects sensitivity and estimates of front-end attenuation need to take this into 

account.

xviii
EFFECTS OF BROADBAND RADIO SERVICE REALLOCATION ON 2900–3100 MHZ 

BAND MARINE RADARS: FRONT-END OVERLOAD

Robert Achatz, Mark McFarland, Roger Dalke, Geoffrey Sanders, Paul McKenna, Frank 

Sanders, Robert Johnk1

Spectrum reallocations may place broadband radio services (BRS) near spectrum used by 

2900–3100 MHz band marine radars. Signals from the BRS base stations can potentially 

cause the radar front-end to overload and cause interference. This report provides a method

that can be used to estimate front-end filter attenuation required at various radar to base 

station separation distances. The attenuation is the difference between the interfering power 

at the radar low-noise front-end (LNFE) and the allowable interference power. The BRS 

signal was emulated with 10 MHz bandwidth Gaussian noise. The allowable interference 

power IPC is determined from probability of detection measurements with a custom test 

fixture. Two front-ends were tested. One was an off-the shelf magnetron radar front-end

assembly consisting of a circulator, limiter, and low-noise front-end. The other, referred to as 

the reference front-end, was constructed of discrete components. The reference front-end was 

tested without the frequency selectivity of the circulator and limiter. Results showed that the 

allowable interference power is -11.5 and -9 dBm for the reference front-end and magnetron 

front-end assembly, respectively. Additional front-end filtering is not required for either 

front-end at distances as close as 400 meters. Distances less than 400 meters were not 

analyzed due to near-field effects. Gain compression and noise enhancement metrics, which 

are simpler to measure than performance degradation, were also evaluated to determine if 

they could reliably predict allowable interference power. Only the noise enhancement metric 

could reliably predict the performance degradation. This result is important since many frontend overload studies are based on the gain compression point metrics.

Keywords: broadband radio service, front-end filter, front-end overload, gain compression, 

interference, interference protection criteria, marine radar, noise enhancement, 

radar, radio spectrum engineering, radio wave propagation

1 INTRODUCTION

Spectrum reallocation is often necessary to accommodate new services which can potentially 

increase business productivity and enhance the lives of private citizens. However, reallocating 

services to bands near those used by incumbent services—or, in some cases, to those same 

bands—can cause interference to the incumbent service.

Spectrum reallocation can cause interference in radar systems in a number of ways [1], [2], [3], 

[4]. For example, a system moved to a nearby band can introduce unwanted emissions into the 

radar detection bandwidth. Also, emissions from a system reallocated to a nearby band can 

overload the radar receiver front-end (receiver circuits operating at the carrier frequency) and 

1 The authors are with the Institute for Telecommunication Sciences, National Telecommunications and Information 

Administration, U.S. Department of Commerce, Boulder, CO 80305.

 
cause gain compression, increased noise power, and intermodulation in the radar detection 

bandwidth.

The U.S. Coast Guard (USCG) asked the National Telecommunications and Information 

Administration Institute for Telecommunication Sciences (NTIA/ITS) to investigate effects of 

spectrum reallocation on the 2900–3100 MHz band marine radar service by determining 

interference protection criteria (IPC) and analyzing strategies for mitigating the interference.

Results of these investigations are expected to be useful to regulatory and standards bodies which 

are responsible for developing IPC including the NTIA [5]; the International Telecommunication 

Union (ITU) [6]; the International Electrotechnical Commission (IEC) [7], which is currently 

devising IPC tests on behalf of the United Nations Maritime Safety Committee (UN/MSC) [8]; 

and the Institute of Electrical and Electronics Engineers (IEEE) [9].

In this series of reports we analyze the effects of reallocation to accommodate broadband radio 

services (BRS) on the 2900–3100 MHz band marine radar service. The BRS is the next 

generation of personal communications services which will provide wideband Internet 

communications to mobile users. Spectrum regulators are currently investigating various 

reallocation strategies to accommodate BRS growth.

Marine radars are used by ships to avoid collisions with objects while traveling in oceans, seas, 

lakes, and rivers. An example of a marine radar antenna mounted on a ship is shown in Figure 1. 

Detection of objects, referred to as targets, is often difficult. Even on calm seas, the target can 

have significant radar cross section (RCS) variation and corresponding reductions in signal 

power. The target can also be obscured by signal reflections or clutter from waves and 

precipitation.

These 2900–3100 MHz band radars are often referred to as S-band marine radars. Similar radars 

that operate in the 9200–9500 MHz band are often referred to as X-band marine radars. The 

primary advantage of S-band radar signals is that they have less precipitation attenuation than Xband radar signals. This allows S-band radars to detect smaller objects at longer distances in 

adverse weather conditions. Large ships subject to international safety of life at sea (SOLAS) 

regulations generally operate with radars in both bands.

BRS providers promise to deliver fast, reliable Internet service to users wherever they are. An 

example of a BRS base station is shown in Figure 2. Potential unwanted emissions and front-end 

overload problems in 2900–3100 MHz band marine radars from BRS base stations were brought 

to the attention of the International Telecommunication Union in November 2009 by the United 

Kingdom [10]. 

Significant amounts of spectrum are needed for widespread BRS use. BRS systems are already 

operating in the 2500–2690 MHz band. The 3500–3650 MHz band has been evaluated for 

reallocation [11]. Other reallocations in the 2700–3700 band, currently allocated to a number of 

radar services as shown in Figure 3, could also affect 2900–3100 MHz band marine radars.

BRS and radar system characteristics are derived from those used by internationally recognized 

groups. The BRS system is modeled after systems devised by the European Technical Standards 

Institute (ETSI) Universal Mobile Telecommunications System (UMTS) committee/3rd 

2
Generation Partnership Project (3GPP) [12], ITU [13], and the WiMAX Forum [14]. The radar 

system is modeled after a system devised by the IEC 62388 standard shipborne radar committee 

[7] for industry acceptance testing.

Figure 1. Marine radar slotted array antenna (white bar) mounted on motor which spins it.

Figure 2. BRS base station.

3
Figure 3. Radio spectrum from 2500 to 3700 MHz with current allocations for air traffic control 

(ATC), weather, marine, and various Department of Defense (DOD) radar services.

1.1 Previous Background Work 

The IPC, scenario, and models needed for interference analysis are provided in the previous 

background report [15] and briefly summarized here. IPC are needed to reduce the probability of 

collision while not placing onerous burdens on other systems using the radio spectrum. Our 

objective is to determine IPC and factors such as distance and frequency separation that can 

mitigate the effects of the interfering signal so IPC can be met. IPC for base station interference 

in the marine radar receiver include:

Radar baseline performance level, signal to noise ratio (SNR), and reliability

Radar allowable degraded performance level, interference power level, and reliability

The physical scenario used for interference analysis is shown in Figure 4. We assume a radar 

target is located between a network of BRS base stations and a ship with a 2900–3100 MHz band 

magnetron marine radar. Weather conditions are assumed to be benign so that there is no signal 

“clutter” from reflections off precipitation or waves.

Radar targets include shorelines, ships, boats, and navigational buoys. The target RCS, which 

varies or fluctuates with time, is modeled with a statistical distribution. The mean of the 

distribution is dependent on target aspect angle, shape, and materials.

The base stations are modeled after those described by ETSI UMTS, 3GPP, ITU, and WiMAX 

groups. BRS signals use orthogonal frequency division multiple access (OFDMA) and are 

transmitted within BRS channels characterized by their center frequency and bandwidth. 

Transmit and receive signals use frequency division duplexing (FDD) so that transmissions can 

occur at all times. The signals are transmitted from antennas that typically cover 60 degree 

azimuth sectors with slant, 45 degree polarization. Although more than one BRS channel can be 

transmitted at one time, we assume only one 10 MHz channel is transmitted.

The radar is modeled after the magnetron radar in the IEC 62388 standard for shipborne radars. 

The radar transmits periodic pulses from a rotating antenna with a narrow antenna beam width 

and horizontal polarization. Typically short, medium, and long pulse widths are used to detect 

targets at different ranges and range resolution. Pulses arriving within the time it takes the 

antenna to traverse its beam width are integrated to enhance SNR. 

4
The interfering radio wave propagation path is the path from the base station to the radar. The 

desired propagation path is the path from the radar to the target and back to the radar. These 

paths can have path loss variation depending on atmospheric conditions, which produces power 

fading and enhancement. Path loss variability occurs at longer distances from hour to hour and is 

characterized with a statistical distribution. The ITS Irregular Terrain Model (ITM) radio wave 

propagation model is used because it is able to predict power fading and enhancement caused by 

path loss variability. 

Besides establishing IPC, scenario, and models, the previous background report addressed three 

fundamental interference analysis issues including

5

 BRS signal characteristics: BRS emissions from a single base station can be reasonably

modeled with Gaussian noise. Since its statistics are Gaussian it follows that emissions from

an aggregate of base stations will also be Gaussian.

 Aggregate interfering emissions: The interfering signal is the sum of signals from an

aggregate of base stations, the mean power and distribution of the aggregate emissions can be

determined using ITM and Monte Carlo analysis, and the aggregate emissions from 10 base

stations spaced 3 km apart could have as much as 6 dB more power at some distances as

compared to a single base station.

 Variable SNR: Interference analysis for scenarios with long radar to target ranges need to

account for a variable radar SNR caused by atmospheric conditions that vary from hour to

hour. While devising a method for incorporating variable SNR we found that there was a

considerable amount of excess power in radar to target link budgets used in acceptance tests.

Although this excess SNR could potentially mitigate interference we found that it is needed

to accommodate reductions in target mean RCS due to different target aspects, shapes, and

materials. We recommended removing the excess power prior to interference analysis by

reducing the mean RCS.
Figure 4. Physical layout showing a network of BRS base stations contributing to the interfering 

signal power. The interference can cause the radar to not detect the target. Antenna pattern 

attenuation is not represented in this figure.

1.2 Report Organization

This report determines allowable interference power IPC, front-end filter attenuation, and 

separation distances needed to prevent overload. The allowable interference power IPC is 

determined from probability of detection measurements with a custom test fixture. Results are 

compared to commonly used overload metrics such as receiver front-end gain compression 

which are easier to execute than probability of detection measurements. 

The general problem is discussed in Section 2. Our approach to solving the problem is provided 

in Section 3. A mathematical description of the method is given in Section 4. A description of 

the test fixture used in given in Section 5. Results are provided in Section 6. The Appendices 

provide additional information for the interested reader.

6
2 FRONT-END OVERLOAD

Front-end overload is caused by strong signals within the radar front-end bandwidth. As an

example, the interfering PSD in Figure 5 is within the radar front-end bandwidth and there is 

potential for front-end overload. In contrast, the interfering PSD in Figure 6 is mostly outside the 

front-end bandwidth and the potential for front-end overload is greatly reduced.

Front-end overload can be prevented by decreasing the transmitter power, increasing the distance 

separating the base stations from the radar, and/or increasing the frequency separation between 

the base station and radar center frequencies. However, the most expedient way to avoid frontend overload is to use a front-end filter whose bandwidth corresponds to the operating band [16].

Then radar signals within the operating band are unattenuated while signals outside the operating 

band are attenuated. Figure 7 is a general block diagram of the BRS transmitters and radar 

receiver showing the front-end filter located between the limiter and the low-noise amplifier 

(LNA) in the radar receiver block. The purpose of this report is to find the front-end filter 

attenuation needed to prevent overload.

Figure 5. Interfering power spectral density centered at ffii is within the radar front-end bandwidth

(BW) (bold outer dashed line). The radar is vulnerable to front-end overload.

Figure 6. Most of interfering power spectral density centered at ffii is outside of the radar frontend bandwidth (BW) (bold outer dashed line). The radar is protected from front-end overload.

7
Figure 7. General block diagram of BRS transmitters and radar system. TX represents the 

transmitter, TF represents the transmitter filter, TX ANT represents the transmitter filter, ANT 

represents the radar antenna, FEF represents the front-end filter which prevents overload, LNA 

represents the low-noise amplifier, IFF represents the IF filter, and DET represents the threshold 

detector.

8
3 METHOD

The method described here provides a direct measurement of the effect of overload on

probability of detection, PPdd. The results are used to determine the allowable interference power 

and the amount of front-end attenuation needed for a specified separation distance. Frequency 

separation is not determined.

3.1 Effects of Front-End Overload on Pd and Pfa

Our method measures the effect of front-end overload on PPdd using the amplitude probability 

distribution (APD) of the voltages present at the radar detector. The APD characterizes the 

probability that the amplitude of a random signal, AA, will exceed a voltage, yy

PPPP{AA > yy} (1)

and is typically plotted on a Rayleigh graph whose y-axis or ordinate is scaled so the APD of 

complex Gaussian noise is represented by a straight, negatively-sloped line with mean power at 

approximately the 37th percentile [17],[18].

Figures 8 and 9 are renditions of how overload from interference can change the shape of noise 

and signal plus noise APDs. Actual measurements are shown in Appendix A.

Figure 8 shows the APDs in the absence of the interfering signal. The noise APD determines the 

threshold voltage, TT, corresponding to the probability of false alarm, PPff . The PPdd is the signal 

plus noise APD probability corresponding to TT. In this case the PPdd is 0.8 and the PPff is 1x10-4or 

0.01%.

Figure 9 shows these same APDs when an interfering signal that causes overload is present. The 

noise curve departs significantly from the straight noise curve in Figure 8 and its mean is 

elevated. Together these effects require an increase in TT to maintain the same PPff it had without 

interference. This in turn lowers the PPdd.

9
Figure 8. APD of voltages present at the detector when the interfering signal is absent.

Figure 9. APD of voltages present at the detector when the interfering signal is present.

Front-end overload effects in amplifiers such as gain compression and changes in noise statistics 

are well understood when the interfering and desired signals are continuous waves (CW) [19],

[20]. Briefly, gain compression is caused by a third order non-linearity which shifts power to 

intermodulation signal components outside the detection bandwidth. The changes in the noise

10
statistics are caused by a second order non-linearity which shifts low frequency noise to the 

receiver’s center frequency.

The effects are more difficult to analyze when the interfering signal is a random noise process

like the BRS signal and there are more electronic circuits than amplifiers involved. In the marine 

radar there are also circulators, limiters, and mixers that are inherently non-linear devices. 

Consequently we chose to determine the effect of overload through APD measurement rather 

than analysis. 

3.2 Allowable Interference Power

Interference power, (or II in dB), is evaluated at the receiver input. The allowable interference 

power, aa (or IIaa in dB), is the interference power needed to degrade radar performance from 

baseline to allowable. The allowable interference power is determined by calculating PPdd from 

APD measurements over a range of interference powers. An example of a set of these 

measurements, referred to as the degradation point (DP) measurement, is shown in Figure 10.

Figure 10. PPdd over a range of interfering signal powers.

We assume front-end overload is most likely to occur at short radar-to-target ranges where 

propagation path loss variability is negligible and SNR and INR are constant as discussed in the 

previous background report [15]. Consequently, most of the variability is due to RCS fluctuation

and experimental uncertainty is dependent on the number of RCS fluctuations measured. Our 

goal is to use enough fluctuations to detect 5% PPdd degradation corresponding to a -6 dB INR for 

11
unwanted emissions. Using Monte Carlo simulation, described in Appendix B, we determined 

that approximately 400 fluctuations were needed.

Figure 11 is a flow chart of the sequence of steps for this measurement. Briefly, the sequence 

turns off the radar signal, ; sets the interfering signal power, II; collects noise data; and 

determines the TT for the desired PPff from the noise APD. It then turns the radar signal on;

calculates a realization of the Swerling 1 RCS fluctuation factor, kk; sets the radar signal level to 

the product of kk and the baseline SNR; collects signal plus noise data; and determines the PPdd

corresponding to TT from the signal plus noise APD. This is done a number of times with new 

RCS fluctuation factor realizations to reduce uncertainty. The set of PPdd is then averaged.

Mathematical details are provided in Sections 4.2 and 4.1.

Figure 11. Flow chart showing sequence of measurement and data processing steps.

3.3 Separation Distance and Front-End Filter Attenuation

Following the derivation in the previous background report [15], the link budget equation for the 

aggregate interfering signal power at the radar receiver is 

12
( 1) = � ss ssssssss( ) = � ̂

tt gg�ttgg

�llddllbbbb llpppp llcccc

∙ 1

ll

̃

pp, ( )

NN

=1

NN

=1

(2)

where ss ssssssss is the interfering signal power from a single base station, 1 is the distance from 

the radar to the closest base station, is the distance from the nn-th base station to the radar, NN is 

the number of base stations in the aggregate, ̂

tt is the signal power at the transmit antenna, gg�tt is 

the gain of the base station antenna in the direction of the radar, gg is the gain of the radar antenna 

in the direction of the base station, lldd is the radome loss, llbbbb is the integration beam shape loss, 

llpppp is the polarization loss between the base station and radar antennas, llcccc is the radar receiver

circuit loss, and ll

̃

pp, is the path loss from the nn-th base station to the radar.

Finally, the front-end filter attenuation required is 

LLFFFF( 1) = II( 1) − IIaa ( dd) (3)

13
4 MATHEMATICAL FOUNDATIONS

4.1 Target RCS Fluctuation

Radar power returned from one target RCS fluctuation realization can be obtained using the 

method of uniform deviates. The Swerling 1 radar cross section density function is exponential

ff(σσ) = 1

σσaaaa

ee−σσ σσaaaa � , σσ > 0 (1)

with mean σσaaaa and variance σσaaaa

2 . Its corresponding distribution is

FF(σσ) = PPPP{Σ < σσ} = � 1

σσaaaa

ee−xx σσaaaa � dd

σσ

0

= 1 − ee−σσ σσaaaa � (2)

The density function for the uniform distribution is

ff(uu) = �

1

bb − , ≤ uu ≤ bb

0, ee eeeeeehee ee

(3)

and its corresponding distribution function is

(uu) = PPPP{ < uu} = � dd = uu

uu

0

(4)

when bb = 1 , = 0, and 0 ≤ uu ≤ 1.

Setting 

PPPP{Σ < σσ} = PPPP{ < uu} (5)

then

1 − ee−σσ σσaaaa � = uu (6)

kk = σσ

σσaaaa

= − ln(1 − uu) (7)

and the power of jj-th radar cross section realization is

ss,jj = sskkjj (8)

where ss is the mean power.

14
4.2 Interference Measurement Data Processing

4.2.1 Noise Measurement Data Processing

Noise data processing determines the threshold voltage, TT. The noise record consists of 

measurement samples

nnjj, jj = 1, ... JJ (4)

where jj is the measurement sample index and JJ is the number of samples. The non-coherently 

integrated noise envelope is computed from KK noise records by

ηηjj = ��nnjj,kk�

KK

kk=1

(5)

where kk is the integration index and KK is the number of integrations.

The noise APD , PPPP�ηηjj > vv�, estimate is created by sorting the integrated noise from high to low 

into the vector where

[1] > [2] > ⋯ > [JJ] (6)

and pairing the sorted data with probabilities from 1/JJ to 1.0. The voltage threshold is

TT = [mm] (7)

where

mm = �PPff ∗ JJ� (8)

and ⌊∙⌋ is the rounding-down or floor operator.

4.2.2 Received Signal Data Processing

Received signal data processing determines the PPdd. The received signal is = + nn. The 

received signal record consists of measurement samples

jj, jj = 1, ... JJ (9)

where jj is the measurement sample index and JJ is the number of samples. The non-coherently 

integrated received signal envelope is computed from KK noise records by

15
ρρjj = �� jj,kk�

KK

kk=1

(10)

where kk is the integration index and KK is the number of integrations.

The received signal APD, PPPP�ρρjj > yy�, estimate is created by sorting the integrated data from 

high to low into the vector where

[1] > [2] > ⋯ > [JJ] (11)

and pairing the sorted data with probabilities from 1/JJ to 1.0. The probability of detection is

PPdd = mm/JJ (12)

where mm is the largest integer that satisfies

[mm] > TT (13)

The PPdd averaged over all the target RCS fluctuation realizations is 

PPdd = 1

LL�PPdd,

LL

=1

(14)

where ll is the fluctuation index and LL is the number of fluctuations.

4.2.3 Power and Power Ratios

The noise power is 

= 1

JJ

��nnjj�

2

JJ

jj=1

(15)

The signal plus noise power is

= 1

JJ

�� jj�

2

JJ

jj=1

(16)

The signal to noise ratio is

γγ = − (17)

The average SNR over all fluctuations is 

16
γγ = 1

LL�γγ

LL

=1

(18)

where ll is the fluctuation index and LL is the maximum number of fluctuations.

17
5 FRONT-END OVERLOAD TEST FIXTURE

The block diagram in Figure 12 shows key components for analyzing front-end overload. The 

low-noise amplifier (LNA) is considered the most vulnerable to overload. However the circulator 

and limiter are non-linear devices and can also overload. The antenna, circulator, and limiter 

provide some degree of protection to the LNA because of their bandwidth limitations. The frontend filter (FEF) provides the rest.

Figure 12. Radar system block diagram showing key components for analyzing front-end 

overload. FEF represents the front-end filter, LNA represents the low-noise amplifier, MXR 

represents the mixer, and AMP represents the amplifier.

Figures 13 and 14 show a block diagram and a photograph of the test fixture. The aggregate BRS 

signal is emulated with band limited Gaussian noise created by a vector signal generator (VSG). 

The BPF at the output of the VSG attenuates its spurious emissions so they are insignificant in 

the radar bandwidth. The radar signal is emulated by a 3050 MHz CW signal created by a signal 

generator (SG). In using a CW signal, we are assuming that the front-end overload does not 

distort the radar pulse shape. These two signals are combined and applied to the radar front-end

which is placed inside a metal box to reduce noise.

The second signal generator (LO) supplies the 3110 MHz local oscillator signal to the front-end. 

The front-end output is applied to the 60 MHz center-frequency IF section which prepares the 

signal for the vector signal analyzer (VSA), spectrum analyzer (SA), and power meter (PM) data 

collection instruments. For the interested reader, test fixture schematics and specifications are 

provided in Appendix C.

18
Figure 13. Front-end overload test fixture block diagram. From left to right are the vector signal 

generator (VSG), band pass filter (BPF), radar signal generator (SG), combiner/splitter (C/S), 

front-end, local oscillator (LO), intermediate frequency section (IF), and the test instruments 

including the vector signal analyzer (VSA), spectrum analyzer (SA), and the power meter (PM).

Figure 14. Front-end overload test fixture. From top to bottom in the rack are the vector signal 

generator (VSG), vector signal analyzer (VSA), band-pass filter (BPF) (small black box), radar 

signal generator (SG), reference front-end and IF section, magnetron front-end assembly, power 

supplies, local oscillator (LO), and power conditioning unit.

19
5.1 Front-end

Figures 15 and 16 are a photograph and block diagram, respectively, of the magnetron front-end

assembly used in the test fixture. The assembly consists of a circulator, limiter, and LNFE—all 

commercial off-the-shelf components. A terminator replaces the radar transmitter. The 

terminator, circulator, and limiter are waveguide components.

Figure 17 is a block diagram of the LNFE, which consists of a low-noise amplifier (LNA) and a 

two-mixer, image-rejection, frequency down-conversion circuit. The LNFE was modified by the 

manufacturer to accept an external local oscillator signal so that all front-ends could use the same 

local oscillator. 

The magnetron front-end assembly LNFE is sealed and characteristics of the components in it 

are unknown. Consequently, we also chose to design and build what we refer to as a reference 

front-end from discrete components whose characteristics are known. The reference front-end

does not have the filtering by the circulator and limiter that the magnetron front-end assembly 

has. A photograph of the reference front-end is shown in Figure 18. The reference front-end

block diagram is identical to that of the magnetron front-end assembly LNFE in Figure 17.

Figure 15. Magnetron front-end assembly. Components (from left to right) are waveguide 

terminator, circulator, limiter, and low-noise front-end. The signal and interference are applied at 

the SMA to type-N adaptor on the circulator. The local oscillator signal from the signal generator

is applied to the SMA connector on top of the LNFE. The IF signal is taken from the SMA 

connector on the side of the LNFE.

20
Figure 16. Magnetron radar front-end assembly block diagram. CIR represents the circulator, 

LIM represents the limiter, and LNFE represents the low-noise front-end.

Figure 17. Low-noise front-end block diagram. LNA represents the low-noise amplifier, C/S 

represents the combiner/splitter, circle with a cross represents a mixer, and the block with 90o

represents the quadrature combiners/splitters.

21
Figure 18. Reference front-end. Components (from top to bottom) are the LNA, quadrature

splitter, splitter, mixers, and quadrature combiner. The signal and interference are applied to the 

LNA input, the local oscillator signal is applied to the splitter, and the IF signal is taken from the 

quadrature combiner.

5.2 Test Fixture Characterization

Test fixture gain, gain compression, and noise figure measurements were made to characterize its 

operation under normal operation conditions. Procedures for these measurements can be found in 

Appendix D and Appendix E. Comprehensive results using the procedures are presented in 

Appendix F. This section contains highlights of front-end and emulated BRS signal 

characterization results.

5.2.1 Front-end Characterization

Circulator and limiter frequency responses measured with a VNA are shown in Figure 19. The 

least attenuation is over the 2900–3100 MHz marine radar band. When combined, the circulator 

and limiter have an approximately 500 MHz 3 dB bandwidth beginning at 2700 MHz and ending 

at 3200 MHz. Outside this range, limiter attenuation increases steeply as compared to the 

circulator. The circulator has a deep null around 2850 MHz.

22
Front-end gain was measured with a 3050 MHz CW signal in the center of the radar detection 

bandwidth with a power that would not cause overload. Front-end gain compression was 

measured in the same way, with the exception that the power was increased to the 1 dB gain 

compression point (GCP). The 1 dB GCP is the minimum amount of power at which a 1 dB 

increase in input power produces no measurable increase in output power.

Noise powers were too low to be measured without gain from the IF section so they were 

calculated from the system and IF section noise figures. The noise figures were measured using 

the Y-factor method with a noise diode source. With the Y-factor method, noise figure is 

computed from two measurements, with the noise diode turned off and then on.

Figure 20 shows the results of the gain compression measurement. The gain compression curves 

of the reference front-end and magnetron front-end assembly are practically identical. The 1 dB 

GCPs for the reference front-end and magnetron front-end assembly are approximately 2 and 

1 dBm, respectively.

Results for all the characterization measurements are summarized in Table 1. These results show 

that the reference front-end and magnetron front-end assembly have similar characteristics.

Figure 19. Frequency selectivity for circulator, limiter, and their combination. The marine radar 

band extends from 2900-3100 MHz. The radar channel is 60 MHz wide and centered at 3050 

MHz. The interfering BRS signal was tuned to 2720 MHz as indicated by the white dashed line.

The 2500-2690 MHz band is currently used for BRS. The 3500-3650 MHz band is being 

evaluated.

23
Figure 20. Front-end gain compression curves.

Table 1. Gain and noise figure measurement results.

Gain (dB) Input 1 dB GCP (dBm) Noise Figure (dB) Notes

Reference front-end 5.8 2 5.0* * Calculated

Magnetron front-end assembly 6.5 1 5.3* * Calculated

5.2.2 BRS Signal Characterization

The BRS signal is emulated by a 10 MHz wide Gaussian noise signal. The duration of the 

emulated signal exceeds the length of time used to collect one APD measurement. The signal 

begins as a 100 MHz Gaussian noise complex baseband signal. It is then filtered by a 256 tap 

10 MHz bandwidth FIR filter, converted to the VSG format, and loaded into the VSG for 

playback. The VSG shifts the complex baseband signal to the interfering signal center frequency.

The ideal interfering signal frequency would have little circulator and limiter attenuation and a 

large frequency offset from the marine radar band. A large frequency offset is needed so that 

VSG spurious responses can be filtered out before they enter the radar detection bandwidth. 

Figure 19 in the previous section showed 2720 MHz met these qualifications. Hence, we used 

2720 MHz for the interfering signal frequency.

Figure 21 shows the power spectral density (PSD) of the emulated BRS signal at complex 

baseband centered at 0 Hz. The PSD was created by the Welch method using 128 blocks of 

131,072 samples. The Hamming window was used to reduce spectral leakage. The emulated 

24
signal occupies approximately 10 MHz from -5 MHz to 5 MHz. The frequency increment is 

763 Hz.

Figure 21. Power spectral density of emulated BRS signal.

5.3 Instrument Control and Data Processing

Instrument control and data processing tasks were performed with a software algorithm and 

computer. Instrument control consisted primarily of setting VSG and SG powers corresponding 

to interference and radar powers and digitizing signals with the VSA. Details regarding 

instrument control are provided in Appendix G. Data processing consisted of integrating data, 

constructing APDS from the integrated data, and calculating TT and PPdd, from the APDs.

25
6 RESULTS

6.1 Parameters

Parameters for the physical layout, radar, radio wave propagation, target, and BRS system are 

provided in the previous background report [15]. Table 2 summarizes relevant radar and BRS 

parameters.

Table 2. Radar and BRS parameters used for analysis.

Parameter Value Note

̂

tt 13.0 dBW 20 W for 10 MHz channel at antenna

gg�tt 15 dB

gg 27.0 dB

lldd 1.0 dB Two-way

llbbbb 1.6 dB Two-way

llss 0.0 dB

llcccc 2.7 dB

llcc 2.7 dB

llpppp 3.0 dB Radar is horizontally polarized. BRS 

is 45 degree slant cross polarized.

6.2 IPC

Relevant IPC parameters are summarized in Table 3. The baseline SNR is determined without 

signal processing loss. Signal processing loss caused by imperfect matched filtering, sampling, 

and CFAR is not applicable to this experiment, where a CW radar signal is used and the 

threshold is set during analysis.

Tests were conducted with and without pulse integration. With no integration, the baseline SNR 

is 10.98 and 16.05 dB for Swerling 0 (no target fluctuations) and 1 (target fluctuations), 

respectively. Tests with integration used the IEC 62388 long and short pulses at a 40 rpm 

antenna rotation rate. Relevant pulse parameters and baseline SNR are provided in Table 4. More 

detailed information regarding the IEC 62388 pulses can be found in the previous background 

report [15]. 

Table 3. IPC parameters.

IPC Value Note

Baseline performance 0.8 PPdd at 10-4 PPff IEC 62388 clear air, calm sea standard

Allowable performance degradation 0.76 PPdd at 10-4 PPff 5% DP

Reliability 90%

26
Table 4. Baseline SNR for a 1.9 degree beam-width antenna at baseline performance 0.8 PPdd and 

10−4 PPff . PW is pulse width, PRF is pulse repetition frequency, BW is IF filter bandwidth, RR is 

rotation rate, and nnpp is the number of pulses integrated.

Pulse

PW 

(ns)

PRF 

(Hz) BW (MHz) RR (rpm) nnpp

Baseline SNR (dB)

Swerling 0 Swerling 1

Short 50 1800 20 40 14 2.31 7.58

Long 800 785 3 40 6 4.83 10.03

6.3 Preliminary Parameter Study

Effects of radar receiver bandwidth and integration were evaluated to determine how sensitive IIaa

is to pulse parameters in Table 4. The effect of interfering signal characteristics were also 

studied. The nominal measurement to which all others were compared was executed with the 

reference front-end, no target fluctuations (Swerling 0), no integration, 10 MHz bandwidth 

limited Gaussian noise centered at 2720 MHz, and a 4.6386 MHz radar receiver bandwidth.

The effect of receiver bandwidth was evaluated by doubling the receiver bandwidth to 

9.2773 MHz. The effect of integration was evaluated by increasing the number of pulses 

integrated to 6 and then 14. The effect of signal characteristics was evaluated by replacing the 

Gaussian noise with a CW signal at the same frequency.

Results of these experiments are shown in Figures 22 and 23. Doubling the radar bandwidth to 

9.2773 MHz and increasing pulse integration had no significant effect on IIaa. Hence it is unlikely 

that our results will be dependent on the pulse in Table 4 we choose to emulate. Consequently,

integration levels higher than 6 were not measured due to measurement time constraints. The 

results also show that the CW signal IIaa is approximately 3 dB more than the IIaa for the 10 MHz 

bandwidth limited Gaussian noise. Consequently, IIaa is sensitive to signal statistics and it is 

important to do the tests with the emulated BRS signal. 

27
Figure 22. Effect of radar receiver bandwidth and continuous wave (CW) interference on 

reference front-end performance degradation.

Figure 23. Effect of pulse integration on reference front-end performance degradation.

28
6.4 Allowable Interference Power

Figures 24 and 25 show performance degradation for both front-ends, Swerling 0 and Swerling 1 

fluctuations, without integration, and with 6 integrated pulses. Figure 26 highlights the Swerling 

1 fluctuation, 6 integrated pulses results from which we will obtain the IIaa needed to estimate the 

minimum amount of front-end attenuation. These results show that the 5% DP IIaa is 

approximately -11.5 and -9 dBm for the reference front-end and magnetron front-end assembly, 

respectively. 

Figure 24. Effect of Swerling model and integration on reference front-end performance 

degradation.

29
Figure 25. Effect of Swerling model and integration on magnetron front-end degradation.

Figure 26. Reference and magnetron front-end performance degradation for Swerling 1, 6 

integrations.

30
6.5 Aggregate Emissions

Figure 27 shows the aggregate emission power with respect to the distance to the closest base 

station, 1. Power at distances over 1 km is calculated with the ITM [21]. Power at distances 

below 1 km but above the minimum far field distance is calculated with free space loss. The 

minimum far field distance is

ffff = 2 aa

2

λλ (19)

where aa is the antenna maximum aperture and λλ is the wavelength. This expression is valid 

when aa > 1.5λλ [22]. When transmit and receive antennas have different apertures the one with 

the larger aperture will determine the far field distance. Assuming the radar antenna aperture is 

4 meters and the BRS antenna aperture is 1.5 meters, ffff would be determined by the radar 

antenna and is approximately 320 meters at 3 GHz.

Figure 27. Aggregate interference power versus distance for various probabilities that the 

interference power (I) is less than the value on the ordinate (y-axis).

6.6 Front-end Attenuation and Separation Distance

Front-end attenuation needed by the reference front-end at different radar to base station 

separation distances is provided in Table 5. An LLff less than 0 implies that no additional 

attenuation is needed. The results show that the front-end needs no additional attenuation for 

distances as close as 400 meters. Since the magnetron front-end assembly IIaa is 2.5 dB higher,

31
this result would be true for the magnetron front-end assembly as well. Results need to be 

adjusted to accommodate more signals.

Table 5. Filter attenuation required for reference front-end at various distances when the 

allowable interference power is -11.5 dBm. Negative attenuation corresponds to protection.

Distance (km) II (dBm) LLFFFF (dB)

1.0 -23.63 -12.13

0.9 -22.71 -11.21

0.8 -21.69 -10.19

0.7 -20.53 -9.03

0.6 -19.19 -7.69

0.5 -17.61 -6.11

0.4 -15.67 -4.17

6.7 Comparison of 5%DP to GCP and NEP

The 5% DP measurement takes a long time. Consequently the 2720 MHz BRS signal 1 dB GCP 

and 1 dB noise enhancement point (NEP) measurements, which take less time, were performed 

to see if degradation can be measured in a more timely manner. The 2720 MHz BRS signal 1 dB 

GCP is the minimum amount of power at which a 1 dB increase in input power produces no 

measurable increase in output power. The NEP is the minimum amount of input power needed to 

increase the noise floor by 1 dB. Measurement procedure details are provided in Appendix H. 

Results for these measurements are shown in Figures 28 and 29. Table 6 compares the results of 

these measurements along with the in-band 3050 MHz CW 1 dB GCP used to characterize the 

front-end.

The magnetron 2720 MHz 1-dB GCP is 7 dB less than the 5% DP and therefore a poor predictor 

of the 5% DP. The in-band 3050 MHz 1-dB GCP was offset 10 or more dB for both front-ends. 

Furthermore the offset was not consistent. Consequently it is also a poor predictor of the 5% DP. 

The 1-dB NEP is within 1 dB of the 5% DP for both front-ends and appears to be a good 

predictor of the 5% DP.

Table 6. Comparison of various performance metrics.

Front-end

3050 MHz CW 2720 MHz BRS

1-dB GCP (dBm) 1-dB GCP (dBm) 1-dB NEP (dBm) 5%DP (dBm)

Reference 2 -10.5 -11.5 -11.5

Magnetron 1 -2 -8 -9

32
Figure 28. System gain compression.

Figure 29. System noise enhancement.

33
7 CONCLUSION

This report describes a methodology for analyzing magnetron radar receiver front-end overload 

caused by signals from an aggregate of broadband radio service (BRS) base stations transmitting 

at frequencies within the radar front-end bandwidth.

The analysis in this report determines how much front-end filter attenuation is needed for various 

separation distances. The attenuation is the difference between the interfering power at the radar 

low-noise front-end (LNFE) and the allowable interference power. 

The interfering power present at the LNFE is determined with a propagation model and a 

methodology for aggregating the signals from a network of base stations. Because of non-linear 

analytic complexity, allowable interference power, IIaa, is determined by probability of detection 

laboratory measurements.

Two front-ends were examined. The first was an off-the-shelf magnetron radar front-end 

assembly with a circulator, limiter, and low-noise front-end. The second was what we refer to as 

a reference front-end consisting of a low-noise front-end constructed from discrete RF 

components. The reference front-end had approximately the same characteristics as the 

magnetron front-end assembly. However, the reference front-end did not have the filtering 

provided by the magnetron front-end assembly circulator and limiter.

The 5% degradation point (5% DP) measurements found IIaa to be -11.5 and -9 dBm for the 

reference front-end and magnetron front-end assembly, respectively. Propagation analysis 

showed that interference powers were less than -23.6 dBm at a 1 km separation distance from the 

closest base station. Consequently, the front-end does not need filter attenuation for distances as 

close as 400 meters. Distances less than 400 meters were not analyzed due to antenna near field 

effects. Since the magnetron front-end assembly IIaa is greater than the reference front-end’s, this 

result would be true for the magnetron front-end assembly as well.

Gain compression and noise enhancement metrics, which are simpler to measure than the 5% DP

metric, were also evaluated to determine if they could reliably predict IIaa. We found that only the 

noise enhancement metric predicted it for both front-ends. This result is important since many 

front-end overload studies are based on the gain compression metrics.

The results in this report are encumbered with two caveats. First, the results are for an FDD BRS 

base station signal that occupies one 10 MHz BRS channel. Results need to be adjusted to 

accommodate more channels. Second, these results are based on magnetron radar signal 

processing. Additional analysis is needed to assess the impact to solid state radar receivers 

because their signal processing is very different from that in the magnetron radar receivers. The 

signal processing affects sensitivity and estimates of front-end attenuation need to take this into 

account.

34
8 REFERENCES

[1] International Telecommunication Union, “Procedures for determining the potential for 

interference between radars operating in the radiodetermination service and systems in 

other services,” Recommendation ITU-R M.1461-1, July 2003.

[2] International Telecommunication Union, “Tests illustrating the compatibility between 

maritime radionavigation radars and emissions from radiolocation radars in the band 2900–

3100 MHz,” Report ITU-R M.2032, 2003.

[3] F. Sanders et. al., “Effects of RF interference on radar receivers,” NTIA Report TR-06-444, 

September 2006. http://www.its.bldrdoc.gov/publications/2481.aspx

[4] J.E. Carroll, G.A. Sanders, F.H. Sanders, and R.L. Sole, “Case study: Investigation of 

interference into 5 GHz weather radars from unlicensed national information infrastructure 

devices, Part I,” NTIA Technical Report TR-11-473, November 2010.

http://www.its.bldrdoc.gov/publications/2548.aspx

[5] A. Paul et. al., “Interference protection criteria,” NTIA Report 05-432, October 2005.

http://www.its.bldrdoc.gov/publications/2462.aspx

[6] International Telecommunication Union, “Studies on frequency-related matters on 

International Mobile Telecommunications and other terrestrial mobile broadband 

applications”, Resolution 233 (WRC-12),The World Radiocommunication Conference 

(Geneva, 2012)

[7] International Electrotechnical Commission (IEC), “Maritime navigation and 

radiocommunication equipment and systems – Shipborne radar – Performance 

requirements, methods of testing and required test results,” IEC 62388, Edition 1.0, 2007-

12.

[8] International Maritime Organization, “Adoption of the revised performance standards for 

radar equipment,” Annex 34, Resolution MSC.192(79), December 6, 2004.

[9] Institute for Electrical and Electronic Engineers, “IEEE recommended practice for the 

analysis of in-band and adjacent band interference and coexistence between radio systems,” 

IEEE Std 1900.2-2008, July 29, 2008.

[10] United Kingdom of Great Britain and Northern Ireland, “Radar adjacent band selectivity,” 

Recommendation ITU-R 5b/389-E, November 18, 2009.

[11] U.S. Department of Commerce, National Telecommunications and Information 

Administration, “An assessment of the near-term viability of accommodating wireless 

broadband systems in the 1675–1710 MHz, 1755–1780 MHz, 3500–3650 MHz, and 4200–

4220 MHz, 4380–-4400 MHz bands,” http://www.ntia.doc.gov/files/ntia/publications/

fasttrackevaluation_11152010.pdf, October 2010.

35
[12] European Telecommunications Standards Institute, “Technical Specification, Digital 

cellular telecommunications system (Phase 2+); Universal Mobile Telecommunications 

System (UMTS); LTE; E-UTRA,UTRA, and GSM/Edge; Multi-Standard Radio (MSR) 

Base Station (BS) radio transmission and reception,” ETSI TS 137 104 version 11.2.1 

Release 11, Oct. 2012.

[13] International Telecommunication Union Joint Task Group 4-5-6-7, Appendix 1 

“Characteristics of terrestrial IMT-Advanced systems for frequency sharing/interference 

analyses” in Attachment 1, “Protection criteria, system characteristics, related materials on 

modelling considerations and sharing studies already performed or underway in ITU-R 

related to the terrestrial services” in Annex 2 “Compilation of material maintained by the 

Joint Task Group 4-5-6-7 working groups” of Report on the Fourth meeting of the Joint 

Task Group 4-5-6-7, Document 4-5-6-7/393-E, October 30, 2013.

[14] WiMAX Forum, “Mobile WiMAX – Part 1: A Technical Overview and Performance 

Evaluation,” WiMAX Forum white paper, August 2006.

[15] R. Achatz, P. McKenna, R. Dalke, N. DeMinco, F. Sanders, and J. Carroll, “Effect of 

broadband radio service reallocation on 2900–3100 MHz band marine radars: 

Background,” NTIA Report TR-15-513, April 2015. http://www.its.bldrdoc.gov/

publications/2795.aspx

[16] U.S. Department of Transportation, Federal Aviation Administration, “Status report: 

Assessment of compatibility of planned Liqhtsquared ancillary terrestrial component 

transmissions in the 1526-1536 MHz band with certified aviation GPS receivers,” Redacted 

Version Cleared for Public Release, January 25, 2012.

[17] R.J. Achatz, “Tutorial on using amplitude probability distributions to characterize the 

interference of ultrawideband transmitters to narrowband receivers,” Appendix A in The 

Temporal and Spectral Characteristics of Ultrawideband Signals, NTIA Report 01-383, 

Jan. 2001. http://www.its.bldrdoc.gov/publications/2414.aspx

[18] M. Cotton, R. Achatz, J. Wepman, and B. Bedford, “Estimating and graphing the 

amplitude probability distribution of complex-baseband signals,” Appendix D in 

“Interference Potential of Ultrawideband Signals, Part 1: Procedures to characterize 

ultrawideband emissions and measure interference susceptibility of C-band satellite digital 

television receivers”, NTIA Report TR-05-419, Feb. 2005. http://www.its.bldrdoc.gov/

publications/2449.aspx

[19] R.G. Meyer and A. K. Wong, “Blocking and desensitization in RF amplifiers,” IEEE 

Journal of Solid-State Circuits, Vol. 30, No. 8, August 1995, pp. 944-946. 

[20] N. Garmendia and J. Protilla, “Study of PM noise and noise figure in low noise amplifiers 

working under small and large signal conditions,” IEEE/MTT-S International Microwave 

Symposium, 2007.

36
[21] G.A. Hufford, A.G. Longley, and W.A. Kissick, “A Guide to the use of the ITS irregular 

terrain model in the area prediction mode,” NTIA Report 82-100, April 1982.

http://www.its.bldrdoc.gov/publications/2091.aspx

[22] N. DeMinco, “Propagation loss prediction considerations for close-in distances and lowantenna height applications,” NTIA Report TR-07-449, July 2007.

http://www.its.bldrdoc.gov/publications/2486.aspx

37
9 ACKNOWLEDGEMENTS

This work was sponsored by the U.S. Coast Guard Spectrum Management Telecommunications 

Policy Division, U.S. Coast Guard CG-652, 2100 2nd St. SW Stop 7101, Washington DC 20593-

7101. The authors would like to acknowledge Fred Mistichelli (former Division Chief), Joseph 

Hersey (former Division Chief), and Daniel Freedman (former Spectrum Engineer) for their 

sponsorship.

The authors would also like to acknowledge David Turnage, Research and Development 

Manager, Kelvin Hughes Ltd., for sharing his insights into this issue.

Finally, the authors would also like to acknowledge Al Romero, Visual Information Specialist, at 

the National Oceanic and Atmospheric Administration (NOAA) for creating the illustrative 

figures, Brent Bedford (ITS) for consultations on test fixture instrumentation, Wayde Allen (ITS) 

for consultations on electromagnetic shielding, and Iris Tobias (ITS) for equipment construction.

38
APPENDIX A: EFFECT OF INTERFERENCE ON APD AND PSD

In this Appendix, reference and magnetron front-end amplitude probability distributions and 

power spectral densities for the Swerling 0 case (without target radar cross section fluctuation) 

with no integration are shown at three interference power levels corresponding to levels where 

interference 1) had no measurable effect on PPdd = 0.8, 2) caused PPdd to degrade to 0.75 or less, and 

3) caused PPdd to degrade to 0.5 or less. The SNR to achieve PPdd = 0.8 with a PPff = 10-4 for 

Swerling 0 with no integration is 10.98 dB.

The data for the APDs and PSDs in Figures A-1-A-12 was collected with a 5.9375 MHz sample 

rate corresponding to a 4.6386 MHz VSA span. Noise and signal APDs at a bandwidth 

corresponding to the VSA span are constructed from 3,072,000 and 307,200 samples, 

respectively. Only one in three of the samples were used in the APD to assure independence.

Noise and signal complex baseband PSDs are estimated with the Welch method by averaging the 

amplitude of 128 spectrum created from 1024 sample block sizes. A Hamming window with a 

1.36 frequency bin equivalent noise bandwidth was used to limit spectral leakage. The 

corresponding frequency bin and equivalent noise bandwidth are 5798 and 7885 Hz, 

respectively. The spike at the 0 Hz center frequency in the signal plus noise PSDs is the desired 

signal. The magnetron front-end assembly PSDs have three discrete spikes on either side of the 

center frequency. The amplitude and frequency of the spikes do not change with interference 

power level.

The results in Table A-1 show that degradation in the reference front-end is due to a combination 

of gain compression, i.e. decreasing , and noise enhancement, i.e. increasing TT. The noise 

APDs show a definite increase in impulsiveness corresponding to increased interference power at 

percentiles exceeding 0.01%. This effect is more pronounced in the magnetron front-end. 

Changes in the PSD are not evident.

Table A-1. Power levels and probability of detection for reference front-end and magnetron 

front-end assembly.

Front-end II (dBm) SS (dBm) NN (dBm) SS

NN� (dB) VVTT (dBm) PPdd

Reference -25 -38.7 -49.7 11.0 -40.8 0.7979

Reference -15 -39.0 -49.8 10.7 -40.1 0.7366

Reference -12 -39.6 -49.5 10.0 -39.5 0.5177

Magnetron -25 -38.1 -49.2 11.1 -39.5 0.8155

Magnetron -10 -38.3 -48.9 10.7 -39.1 0.7119

Magnetron -9 -38.3 -48.7 10.4 -36.9 0.2375

39
Figure A-1. Reference front-end APD at II = -25 dBm.

Figure A-2. Reference front-end PSD at II = -25 dBm.

40
Figure A-3. Reference front-end APD at II = -15 dBm.

Figure A-4. Reference front-end PSD at II = -15 dBm.

41
Figure A-5. Reference front-end APD at II = -12 dBm.

Figure A-6. Reference front-end PSD at II = -12 dBm.

42
Figure A-7. Magnetron front-end assembly APD at II = -25 dBm.

Figure A-8. Magnetron front-end assembly PSD at II = -25 dBm.

43
Figure A-9. Magnetron front-end assembly APD at II = -10 dBm.

Figure A-10. Magnetron front-end assembly PSD at II = -10 dBm.

44
Figure A-11. Magnetron front-end assembly APD at II = -9 dBm.

Figure A-12. Magnetron front-end assembly PSD at II = -9 dBm.

45
APPENDIX B: UNCERTAINTY

Measurement uncertainty considerations determined the number of APD points and target RCS 

fluctuations. This Appendix describes how we calculated these numbers. 

Each measurement begins by obtaining the voltage threshold quantile, TT, corresponding to the 

probability of false alarm, ff , from a measured noise APD

TT = [κκ] (B-1)

where

κκ = �NN ff � (B-2)

⌊∙⌋ is the integer floor operator, and NN is the number of APD samples.

The true probability corresponding to TT is

= PPPP{ > TT} (B-3)

whereas the estimated probability is 

̂= κκ

NN

We want to find NN and an interval [ −, +] so that 

PPPP{ − < < +} = cc (B-4)

i.e. [ −, +] is the cc ∙ 100 % confidence interval.

We begin with the known probability distribution of the estimate ̂and set [B-1],[B-2]

PPPP{ ̂

− < ̂< ̂+} = cc (B-5)

where

̂

− = − zz� pp⁄NN (B-6)

̂

+ = + zz� pp⁄NN (B-7)

= 1 − (B-8)

zz is the number of standard deviations and the standard deviation of ̂is

� pp⁄NN. (B-9)

The number of standard deviations and confidence are related by

46
Φ(zz) = 1

√2ππ

� ee−tt2⁄2 dd

zz

−∞

= 1 + cc

2 (B-10)

z = Φ−1 �

1 + cc

2 � (B-11)

Simplifying (B-6) and (B-7) to 

̂= ± zz� pp⁄NN (B-12)

subtracting from both sides, squaring, and rearranging into quadratic terms with respect to 

� NN

NN + zz2� 2 − �2 ̂+

zz2

2NN� + ̂

2 = 0 (B-13)

solving with the quadratic formula, and factoring we arrive at [B-3]

= � NN

NN + zz2�� ̂± zz� ̂�NN +

zz2

4NN2 +

zz2

2NN� (B-14)

Expanding the first term into a Taylor series yields

NN

NN + zz2 = 1

1 + zz2

NN

= 1 − zz2

NN ⋯ = 1 − �

1

NN� (B-15)

where (∙) is the order operator characterizing extinction rate. Factoring and expanding one of 

the square root terms into a Taylor series 

zz�pp�qq�

NN

+ zz2

4NN2 = zz�pp�qq�NN �1 + zz24pp�qq�NN= zz�pp�qq�NN �1 − �

1

NN�� (B-16)

we have 

= �1 − �

1

NN��� ̂+ zz� ̂�NN �1 − �

1

NN�� +

zz2

2NN� (B-17)

For large NN ≫ zz the approximate lower and upper bounds for the cc ∙ 100 % confidence interval 

are

− = ̂− � ̂�⁄NN Φ−1 �

1 + cc

2 � (B-18)

and 

47
+ = ̂+ � ̂�⁄NN Φ−1 �

1 + cc

2 � (B-19)

The corresponding lower and upper and bounds for the amplitude rank order indexes are 

kk− = �NN ̂− �NN ̂�Φ−1 �

1 + cc

2 �� (B-20)

and 

kk+ = �NN ̂+ �NN ̂�Φ−1 �

1 + cc

2 �� (B-21)

Figures B-1 and B-2 show how the confidence interval changes when NN is 106 and PPff is 10-4. At 

68% confidence, [ −, +] = [0.00009, 0.00011], [kk−, kk+ ] = [90, 110], and the fractional error is 

approximately 10%. The number of points can be decreased by an order of magnitude when 

measuring PPdd which is of little concern below 10-3.

Figure B-1. APD uncertainty in number of points when 106 points are used with a 10-4 event 

probability. Vertical lines at 68.3 and 95.5 percent represent one and two standard deviations 

respectively.

48
Figure B-2. APD uncertainty in fractional uncertainty when 106 points are used with a 10-4 event 

probability. Vertical lines at 68.3 and 95.5 percent represent one and two standard deviations 

respectively.

The number of target RCS fluctuations is determined from the uncertainty in the mean power. 

This uncertainty is evaluated by the standard deviation of the mean

σσMM = σσ

√NN (B-22)

where σσ is the standard deviation of the underlying Swerling 1 process. Figure B-3 shows how 

σσMM decreases with the number of fluctuations. Approximately 400 fluctuations are needed to 

reduce σσMM from 1 to 0.05 which corresponds to a 5% error or a 0.44 dB mean power deviation.

49
Figure B-3. Standard deviation of the mean power estimate as a function of the number of 

Swerling fluctuations.

A Monte Carlo simulation for Swerling 1 target RCS fluctuation with six integrations was 

performed to verify test fixture performance with these parameters. Figures B-4 and B-5 show 

the results of this simulation. The simulation was done without interference and non-linear 

effects. One million APD points were used to determine PPff and one hundred thousand points 

were used to determine PPdd. A 10.03 dB theoretical SNR is needed to achieve 0.8 and 10-4 for PPdd

and PPff , respectively. The estimated PPdd and SNR at the end of 1000 trials are 0.79 and 10.1 dB, 

respectively.

50
Figure B-4. Monte Carlo mean SNR results.

Figure B-5. Monte Carlo mean PPdd results.

51
B.1 References

[B-1] R. Dalke, “Statistical Considerations for Noise and Interference Measurements,” NTIA 

Technical Report TR-09-458, November 2008. http://www.its.bldrdoc.gov/

publications/2495.aspx

[B-2] J. Walsh, Handbook of Nonparametric Statistics, Princeton, N.J., D. Van Nostrand 

Company, Inc., 1962, p. 193.

[B-3] H. Cramer, Mathematical Methods of Statistics, Princeton, N. J., Princeton University 

Press, 1954, p. 515.

52
APPENDIX C: SCHEMATICS AND SPECIFICATIONS

Figure C-1. Front-end overload test fixture with component, cable (Cx), and test point (TPx) 

identifiers. VSG represents the vector signal generator, BPF represents the band-pass filter, SG 

represents the signal generator, C/S represents the combiner/splitter, LO represents the local 

oscillator, VSA represents the vector signal analyzer, SA represents the spectrum analyzer, and 

PM represents the power meter.

Table C-1. Front-end overload test fixture components.

Identifier Name Model number Notes

VSG Vector signal generator Agilent E4438c S/N SG45090178

SG Signal generator Hewlett Packard 8648c

LO Signal generator Hewlett Packard 8341b

BPF Tunable bandpass filter Texscan 5VF 2000/4000

C/S Combiner/Splitter Mini-Circuits ZAPD-4-S+

VSA Vector signal analyzer Agilent 89600S S/N US43490919

SA Spectrum analyzer Hewlett Packard 8562A

PM Power meter Agilent E4417A

IF Intermediate Frequency section Built at ITS

Rubidium clock Lucent RFTGm-11-Rb Connected to SG, LO, VSA, 

VSG, and SA

53
Figure C-2. Magnetron front-end assembly with test points (TP). CIR represents the circulator, 

LIM represents the limiter, and LNFE represents the low-noise front-end.

Table C-2. Magnetron front-end assembly components.

Identifier Name Model number Notes

CIR Circulator New Japan Radio NJC3311A Waveguide

TERM Waveguide WR284 to N adaptor terminated with 

50ohm load

Advanced Technical Materials

PNR 284-253A

LIM Limiter New Japan Radio NJS6318 Waveguide

LNFE Low-noise front-end New Japan Radio NJS4310D

54
Figure C-3. Reference front-end with test points (TP). LNA represents the low-noise amplifier, 

90o represents the quadrature combiner/splitter, C/S represents the combiner/splitter, and circles 

with a cross represent a mixer. The mixing stage is implemented with two mixers, M1 and M2, 

to attenuate noise at image frequency.

Table C-3. Reference front-end components.

Identifier Name Model number Notes

ARF Low-noise Amplifier Mini Circuits ZX-606013E-S+

YRF1 900 Combiner/Splitter Mini Circuits ZAPDQ-4-S

YRF2 Combiner/Splitter Mini Circuits ZMSCQ-2-90

YRF3 900 Combiner/Splitter Mini Circuits ZAPD-4-S+

M1 and M2 Mixer Mini Circuits ZX-05C42CH-S+

55
Figure C-4. IF section. LPF represents the low pass filter and BPF represents the BPF.

Table C-4. IF section components.

Identifier Name Model number Notes

FIF1, FIF2 Low pass filter Mini-Circuits SLP-100+ 100 MHz bandwidth

AIF1, AIF2 Amplifier Mini-Circuits ZFL-500+

PIF Attenuator

FIF3 Band pass filter Mini-Circuits SBP-60+ 20 MHz bandwidth

56
APPENDIX D: POWER MEASUREMENT AND CALIBRATION

D.1 Sine Wave Power Measurement

• The spectrum (SA) or vector signal analyzer (VSA) is used to measure sine wave power 

so that the bandwidth can be restricted and noise eliminated as much as possible from the 

measurement. The sine wave should be well above (30 dB) the noise floor. Auto-couple 

span, sweep time, and video bandwidth. Peak and RMS detector should give same result 

for sine measurement. Measure with peak search function.

D.2 Noise Power Measurement

• The power meter (PM) is used to do noise measurements.

• SA or VSA can also be used to do average noise power measurements. RMS voltage 

detection is the preferred method.

• If using an SA without RMS voltage detection, the measurement can be made with 

analog or digital video averaging. However, the displayed value will be lower than the 

actual value and must be corrected

PPaaaa = PPSSSS + 1.05 + 1.45 ( dd) − 0.5 ( dd) (D-1)

where 1.05 dB compensates for envelope detection, the 1.45 dB compensates for the log 

amplification, and the -0.5 dB converts the Gaussian filter 3 dB bandwidth to an 

equivalent noise bandwidth.

D.3 Signal Generator Power Verification

1. Make sure the signal generator (SG), vector signal generator (VSG), VSA, SA, and PM have 

up to date certifications.

2. Calibrate VSG using I/Q>User Cal>Set Range

3. Set VSG or SG to generate a -30 dBm sine wave.

4. Measure power with PM.

5. Note any deviation.

57
APPENDIX E: CHARACTERIZATION PROCEDURES

This section describes gain and noise figure characterizations for the front-end (FE) and

intermediate frequency (IF) sections. The FE and IF combined is referred to as the system.

E.1 IF Gain and Gain Compression

1. Estimate IF gain, ii , from component specifications.

2. Estimate output 1 dB compression point from component specifications.

3. Estimate the input 1 dB compression point.

PPii ,1dddd = PP ,1dddd − ii ( dd) (E-1)

4. Measure cable loss of input, LL1, and output, LL2, cables at the IF frequency.

5. Set signal generator (SG) to generate sine wave.

6. Set SG to IF frequency.

7. Set SG to a power, PPSSSS, that will generate a power at the spectrum analyzer, PPSSSS, well above 

spectrum analyzer noise floor. Check to make sure it will not overload last IF amplification 

stage.

8. Set up equipment as shown in Figure E-(a).

9. Measure power, PPSSSS

′ , without IF section.

PPSSSS

′ = PPSSSS − LL1 − LL2 ( dd) (E-2)

10. Set up equipment as shown in Figure E-(b).

11. Measure power, PPSSSS, with IF section.

12. Calculate input power, PP1, and output power, PP2.

PP1 = PPSSSS − LL1 ( dd) (E-3)

PP2 = PPSS + LL2 ( dd) (E-4)

13. Calculate IF gain

ii = PP2 − PP1 ( dd) (E-5)

ii = PPSSSS − PPSSSS

′ ( dd) (E-6)

14. Set PPSSSS so that PP1 is 20 dB below estimated 1dB compression point.

58
PPSSSS = PP1 + LL1 ( dd) (E-7)

15. Measure PPSSSS and calculate PP2.

PP2 = PPSSSS + LL2 ( dd) (E-8)

16. Repeat, increasing PPSSSS in 1 dB steps, until PPSSSS does not change.

17. Plot input power, PP1, versus output power, PP2.

E.2 FE Gain and Gain Compression

1. Estimate FE gain from component specifications.

2. Estimate output 1 dB compression point from component specifications.

3. Estimate the input 1 dB compression point.

4. Set SG to generate sine wave.

5. Set SG to RF frequency.

6. Set SG to a power, PPSSSS, that will generate a power at the spectrum analyzer, PPSSSS, well above 

spectrum analyzer noise floor. Check to make sure it will not overload the FE.

7. Measure cable loss LL1 at the RF frequency.

8. Measure cable loss LL2 at the IF frequency.

9. Set up equipment as show in Figure E-(c).

10. Measure PPSSSS.

11. Calculate RF gain.

ff = PP2 − PP1( dd) (E-9)

ff = PPSSSS−PPSSSS + LL2 + LL1 ( dd) (E-10)

12. Set PPSSSS so that PP1 is 20 dB below estimated 1dB compression point.

PPSSSS = PP1 + LL1 ( dd) (E-11)

13. Measure PPSSSS and calculate PP2.

PP2 = PPSSSS + LL2 ( dd) (E-12)

14. Repeat by increasing PPSSSS in 1 dB steps until PPSSSS does not change.

59
15. Plot input power, PP1, versus output power, PP2.

E.3 System Gain and Gain Compression

1. Set up equipment as shown in Figure E-1(d).

2. Measure system gain, ssssss, and gain compression the same as was done for the FE.

3. Compare to ssssss calculated from

ssssss = ii + ff − LL3 ( dd) (E-13)

Figure E-1. Gain measurement configurations. SG represents the signal generator and SA 

represents the spectrum analyzer.

E.4 IF Noise Figure

1. Set up equipment as shown in Figure E-2(a).

2. Turn noise diode (ND) off and measure power at IF output, PPOO .

60
3. Turn ND on and measure power at IF output, PPOO .

4. Calculate noise figure

FFii = EE EE − 10 log10 �

PPOO

PPOO

− 1� ( dd) (E-14)

where EE EE is the noise diode excess noise ratio in dB.

E.5 System and FE Noise Figure

1. Set up equipment as shown in Figure E-2(b).

2. Connect IF section.

3. Measure system noise figure, FFssssss, using ND as is done for IF.

4. Calculate the noise figure of the FE alone by 

ffff = ffssssss − ffii − 1

ggff

(E-15)

FFff = 10 log10�ffff � ( dd) (E-16)

Figure E-2. Noise figure measurement configurations. ND represents the noise diode and PM 

represents the power meter.

61
APPENDIX F: CHARACTERIZATION RESULTS

This section contains test fixture characterization results for reference and magnetron front-ends.

The results include gain, gain compression, and noise figure for the IF section, front-end, and 

system. In this section, gain and gain compression are measured with a continuous wave signal 

in the radar detection bandwidth. The 1-dB compression points are reported as input powers.

Tables F-1–F-3 show how IF gain, FE gain, and system gain are computed. Figures F-1–F-3

show how IF, FE, and system gain changed with input power. Finally, Tables F-4–F-6 show IF, 

system, and FE noise figures.

The IF 1 dB gain compression point is -25 dBm, both FE 1 dB gain compression points are

-1dBm, and both system gain compression points are -32 dBm. Since the system GCPs are the 

same as the IF GCP minus the FE gain, we can conclude that the compression point for signals 

within the radar detection bandwidth is determined by the IF section.

Table F-1. IF gain.

Parameter Value Calculation

PPSSSS (dBm) -15.0 -15.0

LL2 (dB) 0.2 0.2

PPSSSS (dBm) -60.0 60.0

LL1 (dB) 0.2 0.2

II (dB) 45.4

Figure F-1. IF gain compression.

62
Table F-2. FE gain.

Parameter Reference Value

Reference 

Calculation Magnetron Value

Magnetron 

Calculation

PPSSSS (dBm) -45.67 -45.67 -45.0 -45.0

LL2 (dB) 0.2 0.2 0.2 0.2

PPSSSS (dBm) -50.0 50.0 -50.0 50.0

LL1 (dB) 1.3 1.3 1.3 1.3

FFFF (dB) 5.83 6.5

Figure F-2. FE gain compression.

Table F-3. System gain.

Parameter Reference Value

Reference 

Calculation Magnetron Value

Magnetron 

Calculation

ii (dB) 45.4 45.4 45.4 45.4

ff (dB) 5.83 5.83 6.5 6.5

LL3 (dB) 0 0 0 0

ssssss (dB) 51.2 51.9

63
Figure F-3. System gain compression.

Table F-4. IF noise figure. Measured in 20 MHz IF bandwidth.

Parameter Value

PP (dBm) -34.4

PP (dBm) -50.0

FFii (dB) 5.4

Table F-5. System noise figure. Measured in 20 MHz IF bandwidth.

Parameter Reference value Magnetron value

PP (dBm) -29.7 -28.7

PP (dBm) -44.3 -43.2

FFssssss (dB) 5.85 5.95

Table F-6. Calculated FE noise figure.

Parameter Reference value Magnetron value

FFssssss (dB) 5.85 5.95

FFii (dB) 5.4 5.4

ff (dB) 5.83 6.5

FFff (dB) 5.04 5.3

64
APPENDIX G: VSG AND VSA SETUP

G.1 VSG Setup

The vector signal generator (VSG) provides the interfering signal. The interfering signal can 

originate from an internal generator within the VSG or a custom waveform file loaded into the 

VSG non-volatile waveform memory (NVWM) by the user. The internal generator could not 

provide the band limited Gaussian noise used to emulate the broadband radio service signal. 

Consequently we used a custom waveform file.

Automatic level control (ALC) is not possible with the widely varying Gaussian noise voltages. 

However, the average power can be monitored with the power detection loop. The only 

precaution necessary is to decrease power loop attenuation to compensate for the lower average 

power due to the Gaussian noise signal high peak to average power.

To manually set up the VSG:

1. Reset

2. Chose waveform

If using a waveform:

• If waveform is not loaded from NVWM:

Mode>dual arb>select waveform>waveform segments> select waveform using dial or 

arrows >load segment from NVWM memory>return >highlight waveform using dial or 

arrows >select waveform

• Else if waveform is loaded from NVWM

Mode>Dual arb> select waveform >highlight waveform using dial or arrows >select 

waveform

• If Gaussian noise or other signal with high peak to average ratio

 Mode>Dual arb> arbsetup>mod atten set to manual and 6 dB.

 Amplitude>ALC set to off, power search set to auto, power search reference set to 

modulated

 Mode> Dual arb>Arb on

If using modulation buttons:

• Select modulation on front panel

• Mod on button

65
If using a continuous wave:

• No need to do anything

3. Set frequency and amplitude

• Frequency> set to RF center frequency

• Amplitude> set to desired amplitude.

Maximum amplitude is 20 dBm - 3 dB -peak/average in dB

4. Turn on RF

G.2 Creating Interfering Signal for the VSG

1. Create signal with MATLAB®

2. Save as .mat file

3. Run MATLAB program “Mat2Bin4VSG” to convert *.mat file to VSG binary *.bin file

4. Run MATLAB program “NormLargeBinFile4VSG” to convert *.bin file to normalized VSG 

binary file *.nor file

5. Use FTP to transfer *.nor file to VSG

G.3 VSA SETUP

To manually setup the VSA

1. Starting VSA

• Unplug and plug in Firewire, power up VSA, start VSA software

2. Calibrate

• Utilities>Single Cal

3. Modify setup 

• Measurement setup> Center frequency, Span, Resolution bandwidth, Data segment 

length

• Input>Record>Record length

• Input> Input range

• File>Save>Save setup

4. Make recording

66
• Input>Data from hardware

• Input>Range

Adjust to the highest level without overload when interference is present

• Control>Restart

• Control>Record

• File>Save>Save recording

• File naming convention: (Hardware configuration, VSG frequency, VSG power 

level).mat

G.3.1 VSA Setup Parameters 

• Aliased cardinal span is

cc = ffss

2 (G-1)

where ffss is the primary sampling rate and nn is the cardinal span index.

• Usable or unaliased span is

= cc

1.28 (G-2)

• The time increment is 

∆ = 2

ffss

(G-3)

• The segment duration (mean time length) is

ssssss = NNssssss ∙ ∆ (G-4)

where NNssssss is the number of points in a segment

• The frequency spacing is 

∆ff = 1

ssssss

(G-5)

• The total duration is 

= MM ∙ ssssss (G-6)

where M is the number of segments collected.

67
• The total number of points is

NN = MM ∙ NNssssss (G-7)

• For example, assuming a 95 MHz ffss

 If nn is 4, the cardinal span is 5.9375 MHz, the span is 4.638672 MHz, and ∆ is 

168.421 ns.

 If NNssssss is 1024, ∆ff is 5798.3 Hz, and ssssss is 172.463 μs

 If MM is 3000, T is 0.5173 seconds, and NN is 3,072,000.

G.4 VSA Overload

The VSA can detect and report overloading, i.e. non-linear effects caused by strong signals, 

across its entire front-end bandwidth. Since the front-end bandwidth is greater than the 

measurement span, it is possible for the VSA to report overloading even though signals in the 

measurement span are within the instrument’s dynamic range. Our policy is to monitor overload 

and not use data if it is detected.

G.5 SG and VSG Power Setting

This section describes how SG output power, PPSSSS, and VSG output power, PPVV , are set relative 

to system noise power. Noise and signal power are also computed at the VSA input. In the 

calculations noise, NN, signal, , and interference, II, powers are those at the front-end (FE) input.

Figure G-1 shows the front-end overload test fixture and parameters relevant for setting the 

powers.

Figure G-1. Front-end overload test fixture. VSG represents the vector signal generator, BPF 

represents the band-pass filter, SG represents the signal generator, C/S represents the 

combiner/splitter, LO represents the local oscillator, VSA represents the vector signal analyzer, 

SA represents the spectrum analyzer, and PM represents the power meter. LLSSSS, LLVV , and LLOOOO

represent various losses.

68
1. Calculate noise power 

NN = kk + FFssssss + ( dd ) (G-8)

where FFssssss is the system noise factor referred to the FE input and is the radar noise 

equivalent bandwidth. In this case the radar noise equivalent bandwidth is equal to the 

VSA span.

2. Calculate PPSSSS

PPSSSS = + NN + KK + LLSSSS + LL ( dd ) (G-9)

where SNR is the mean SNR over all target RCS fluctuations, K is the random Swerling 

radar cross section target RCS fluctuation factor, LSG, is the loss from the SG to the FE, 

and Lmisc are miscellaneous losses added to achieve baseline performance.

3. Calculate PPVV

PPVV = II + LLVV ( dd ) (G-10)

where LLVV is the loss from the VSG to FE.

4. The noise power at the instrument input is 

PPVV = NN + ssssss ( dd ) (G-11))

where ssssss is the gain from the FE input to the instrument input. LL was negligible.

5. The signal power at the instrument input is 

VV = + NN + ssssss ( dd ) (G-12)

LL was also negligible.

The following tables show how NN, PPSSSS, PPVV , NNVV , and VV were computed for this test fixture. 

They are followed by calculations of signal and noise power measured by the VSA.

Table G-1. Noise power calculation.

Parameter Units

Value

Reference Magnetron Note

kk dBm/Hz -174 -174

FFssssss dB 5.85 5.95

dB-Hz 66.65 66.65 4.63 MHz VSA span

NN dBm -101.5 -101.4 FE input

69
Table G-2. Swerling 0 no integration PPSSSS calculation.

Parameter Units

Value

Reference Magnetron Note

dB 10.98 10.98 Swerling 0 no integrations (see Table G-6)

KK dB 0 0 Swerling RCS fluctuation factor

NN dBm -101.5 -101.4

LLSSSS dB 4.5 4.5 Measured 12/18/12

LL dB 0.5 -0.5

PPSSSS dBm -85.52 -86.42 SG1 output

Table G-3. PPVV calculation.

Parameter Units Value Note

II dBm -20

LLVV dB 5.8 Measured 12/18/12

PPVV dBm -14.2 VSG output

Table G-4. Noise power measured by VSA in 4.63 MHz span calculation.

Parameter Units

Value

Reference Magnetron Note

NN dBm -101.5 -101.4 FE input

ssssss dB 51.2 51.9

NNVV dBm -50.3 -49.5 VSA input

Table G-5. Swerling 0 no integration signal power measured by VSA calculation.

Parameter Units

Value

Reference Magnetron Note

dB 10.98 10.98 Swerling 0 no integration (see Table G-6)

KK dB 0 0 Swerling RCS fluctuation factor

NN dBm -101.5 -101.4

dBm -90.52 -90.42

ssssss dB 51.2 51.9

VV dBm -39.32 -38.52 VSA input

Table G-6. Mean SNR required without the interfering signal for various Swerling types and 

number of integrations.

Swerling type Integrations SNR (dB) 

0 1 10.98

1 1 16.05

70
Swerling type Integrations SNR (dB) 

0 6 4.83

1 6 10.03

0 14 2.31

1 14 7.58

71
APPENDIX H: INTERFERING SIGNAL GAIN COMPRESSION AND NOISE 

ENHANCEMENT MEASUREMENT SET UP

Interfering signal gain compression and noise enhancement were measured with the front-end 

overload test fixture. A block diagram of the test fixture is shown in Figure H-1.

Figure H-1. Front-end overload test fixture block diagram. From left to right are the vector signal 

generator (VSG) which creates the BRS signal, band pass filter (BPF), power combiner/splitter 

(C/S), radar signal CW generator (SG), front-end, local oscillator (LO), intermediate frequency 

section (IF), and the test instruments including the vector signal analyzer (VSA), spectrum 

analyzer (SA), and the power meter (PM).

The radar signal is generated by the signal generator (SG) and the interfering signal is generated 

by the vector signal generator (VSG). To measure gain compression the radar signal amplitude is 

set well above the level that would be used for performance degradation measurements, but not 

so high that it would contribute significantly to front-end overload or cause the IF section to 

overload. With our test fixture we chose a -75 dBm radar signal amplitude at the front-end input.

The radar signal amplitude was measured at the output of the IF section with a SA each time the 

interfering power was changed. Noise enhancement was measured in the same way in the 

absence of the radar signal.

Table H-1. Spectrum analyzer settings.

Parameter Setting

Span 500 kHz

Resolution bandwidth 3 kHz

Video bandwidth 3 kHz

Sweep time 200 ms.

Attenuation 0 dB

Reference level -10 dBm

Detector Sample

72
FORM NTIA-29 U.S. DEPARTMENT OF COMMERCE 

(4-80) NAT’L. TELECOMMUNICATIONS AND INFORMATION ADMINISTRATION

BIBLIOGRAPHIC DATA SHEET

1. PUBLICATION NO.

TR-15-515

2. Government Accession No. 3. Recipient’s Accession No.

4. TITLE AND SUBTITLE

Effect of Broadband Radio Service Reallocation on 2900–3100 MHz Band Marine 

Radars: Front-end Overload

5. Publication Date

April 2015 

6. Performing Organization Code

NTIA/ITS.T

7. AUTHOR(S)

Robert Achatz, Mark McFarland, Roger Dalke, Paul McKenna, Frank Sanders, Robert Johnk, 

Geoffrey Sanders

9. Project/Task/Work Unit No.

3105011-300

8. PERFORMING ORGANIZATION NAME AND ADDRESS

Institute for Telecommunication Sciences

National Telecommunications & Information Administration

U.S. Department of Commerce

325 Broadway

Boulder, CO 80305

10. Contract/Grant Number.

11. Sponsoring Organization Name and Address

U.S. Coast Guard Spectrum Management Telecommunications Policy Division

U.S. Coast Guard CG-652,

2100 2nd St. SW Stop 7101

Washington, DC 20593-7101

12. Type of Report and Period Covered

14. SUPPLEMENTARY NOTES

15. ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant bibliography or

literature survey, mention it here.)

Spectrum reallocations may place broadband radio services (BRS) near spectrum used by 2900–3100 MHz band marine 

radars. Signals from the BRS base stations can potentially cause the radar front-end to overload and cause interference. This 

report provides a method that can be used to estimate front-end filter attenuation required at various radar to base station 

separation distances. The attenuation is the difference between the interfering power at the radar low-noise front-end (LNFE) 

and the allowable interference power. The BRS signal was emulated with 10 MHz bandwidth Gaussian noise. The allowable 

interference power IPC is determined from probability of detection measurements with a custom test fixture. Two front-ends 

were tested. One was an off-the shelf magnetron radar front-end assembly consisting of a circulator, limiter, and low-noise 

front-end. The other, referred to as the reference front-end, was constructed of discrete components. The reference front-end 

was tested without the frequency selectivity of the circulator and limiter. Results showed that the allowable interference 

power is -11.5 and -9 dBm for the reference front-end and magnetron front-end assembly, respectively. Additional front-end 

filtering is not required for either front-end at distances as close as 400 meters. Distances less than 400 meters were not 

analyzed due to near-field effects. Gain compression and noise enhancement metrics, which are simpler to measure than 

performance degradation, were also evaluated to determine if they could reliably predict allowable interference power. Only 

the noise enhancement metric could reliably predict the performance degradation. This result is important since many frontend overload studies are based on the gain compression point metrics.

16. Key Words (Alphabetical order, separated by semicolons)

broadband radio service, front-end filter, front-end overload, gain compression, interference, interference protection criteria, 

marine radar, noise enhancement, radar, radio spectrum engineering, radio wave propagation

17. AVAILABILITY STATEMENT

UNLIMITED.

FOR OFFICIAL DISTRIBUTION.

18. Security Class. (This report)

Unclassified

20. Number of pages

95

19. Security Class. (This page)

Unclassified

21. Price:

N/A
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