Ranging, detection and resolving in a multislope frequency modulated waveform radar system

A maximum likelihood estimator and range-only-initialization target detection method employed to detect and resolve targets in a multislope linear frequency modulated waveform radar. The method resolves a large number of target returns without a large amount of signal processing and without creating a significant number of false alarms, or ghosts. The method simultaneously estimates range and doppler for each target. The method rejects undesired long-range targets that fold into target regions, and processes target regions of interest around a nearest target to reduce signal processing throughput requirements. Using a K out of N detection rule, the method detects targets that compete with mainlobe rain clutter, mainlobe ground clutter, and receiver leakage. The method simultaneously estimates target parameters and optimally resolves any number of targets. The method is limited only by the number of frequency modulation ranging slopes, the slope values, and the doppler filter resolution set by the radar waveform design. The method has the ability to process and detect extended targets.

BACKGROUND 
The present invention relates to radar systems, and more particularly to 
maximum likelihood estimation and range only initialization methods for 
use in multislope linear frequency modulated waveform radar systems. 
Current multislope linear frequency modulated waveform radar processing 
techniques are limited to resolving to small number of targets (not more 
than 4) without a significant increase in ghosts (false alarms). Several 
techniques currently exist for resolving multiple targets in a radar using 
a linear frequency modulated waveform. One computes a target range 
measurement for every possible combination of returns, and another 
provides range and doppler measurements of the target separately. 
Computing all possible combinations needed for target detection requires 
very large amount of signal processing throughput and yields a large 
number of ghosts. The requirement of high throughput results in an 
expensive radar system, and a large number of ghosts creates hazardous 
conditions. With a system providing range measurement only, the velocity 
estimate is derived from differencing consecutive range measurements or 
using filtering. In either case, these estimates require very accurate 
range measurements and introduce unacceptable latencies. 
For automobile applications, such as adaptive cruise control systems, for 
example, large latency introduces additional risks in automobile "cut-in" 
or hazardous situations. A system that separately measures range and 
doppler cannot guarantee that the range and doppler measurements are 
derived from the same target. Again, this results in an adaptive cruise 
control system having a very slow response time. 
Consequently, it is an objective of the present invention to provide for a 
maximum likelihood estimation and range only initialization methods for 
use in multislope linear frequency modulated waveform radar systems that 
provides for the resolution of a large number of target returns without 
extensive signal processing, and without creating a significant number of 
false alarms (ghosts). 
SUMMARY OF THE INVENTION 
In order to meet the above and other objectives, the present invention 
provides for a maximum likelihood estimator and range-only-initialization 
procedure or method that is employed to detect and resolve targets in a 
multislope linear frequency modulated waveform radar, for example, such as 
a frequency modulated continuous wave radar for automobile cruise control 
applications. The present method resolves a large number of target 
returns, typically encountered in a road environment, without a large 
amount of signal processing and without creating a significant number of 
false alarms, or ghosts. The present procedure also simultaneously 
estimates range and doppler for each target. In addition to resolving 
targets, the present method also rejects undesired long-range targets that 
fold into target regions, and has the ability to process target regions of 
interest (to reduce the signal processing throughput requirement) such as 
to a region around a nearest target. Using a K out of N detection rule, 
the present procedure provides the capability of detecting targets that 
compete with mainlobe rain clutter, mainlobe ground clutter, and receiver 
leakage. 
More particularly, the present invention is used in a multislope linear 
frequency modulated waveform radar system comprising means for 
transmitting and receiving radar signals and for processing received 
frequency modulated waveform radar signals to produce magnitude detected 
target signals. The present method of processing the magnitude detected 
target signals to resolve targets corresponding to the magnitude detected 
target signals comprises the following steps. 
The magnitude detected target signals are centroid to provide centroided 
target signals, wherein the detected target signals comprise a set of 
detections observed for each phase (slope segment) of the frequency 
modulated waveform. The centroided target signals are associated using a 
maximum likelihood estimation procedure to predict the filter position for 
the next phase, and wherein the associating step groups the detection from 
each phase by expecting hits to be within a gate size of a projected 
target doppler filter location, and wherein the projected doppler filter 
location and the gate size depend on all previous phase observations. A 
number of targets are eliminated to minimize the number of ghosts by 
reducing the number of candidate targets that correlate in a predetermined 
number of phases by grouping paths with a selected number of common hits. 
The velocity and range for the remaining detected targets are then 
computed. 
As was mentioned above, conventional processing techniques are limited to 
resolving to small number of targets without significantly increasing 
ghosts. However, the present method simultaneously estimates target 
parameters and resolves any number of targets optimally (in a least 
squares sense). Consequently, the present method is limited only by the 
number of frequency modulation ranging slopes, the slope values, and the 
doppler filter resolution set by the radar waveform design. Furthermore, 
the present method significantly reduces the amount of signal processing 
required by the system because it adaptively detects and resolves targets 
in range and doppler regions of interest (for example, the nearest 
target). In addition, the present method has the ability to process and 
detect extended targets, such as large trucks, for example. 
Production of a long range adaptive cruise control system for automobiles 
using frequency modulated continuous waveform radar is made feasible by 
the present invention. Previous systems only provide short range adaptive 
cruise control systems and do not allow timely response in cut-in 
situations. Additionally, the ability of the present method to provide 
instantaneous range and doppler measurement shortens the response time and 
thus permits a collision warning system to be implemented. In airborne 
radar applications, for example, the present invention provides a more 
accurate measurement than current frequency modulated waveform processing 
techniques having the same signal bandwidth.

DETAILED DESCRIPTION 
Referring to the drawing figures, a system diagram of a homodyne 
frequency-modulated continuous-wave (FMCW) radar system 10 is shown in 
FIG. 1. The system 10 is adapted to employ a maximum likehood estimator 
and range-only-initialization method 30 in accordance with the principles 
of the present invention. The radar system 10 is conventional in desing 
and will not be described in detail herein, since such systems are 
well-known in the art. The radar system 10 has two basic components: a 
radar front end 11 and a radar digital signal processor 12. The radar 
front end 11 encompasses that portion of the radar system 10 from a 
transmitting antenna 13a to the output of an analog-to-digital (A/D) 
converter 14. In particular, the radar front end 11 comprises a 
transmitter 15 that is coupled to the transmitting antenna 13a and to a 
local oscillator 16. The transmitter 15 further includes conventional 
timing control and ramp generation circuitry 17. 
The system 10 comprises a receiver 23 that includes a receiving antenna 13b 
is also coupled by way of a mixer 18 to a preamplifier circuit 19. The 
mixer 18 is coupled to the local oscillator 16 and they cooperate to 
downconvert received radar signals to video frequencies. A preamplifier 
circuit 19 is coupled to the output of the mixer 18, which is in turn 
coupled through low-pass and high-pass filtering circuitry 20 that 
provides for filtering for sensitivity control and anti-aliasing of the 
video signals. Amplifiers 21, and automatic gain control (AGC) circuitry 
22 are serially coupled between the output of the low-pass and high-pass 
filtering circuitry 20 and the A/D converter 14. 
The digital signal processor 12 provides for amplitude weighting and 
doppler filter processing 25, for a processing method or procedure 26 that 
implements magnitude detection and thresholding procedure 26 that provides 
for a target detection, and for the multislope frequency modulated target 
resolving procedure 30 in accordance with the principles of the present 
invention. More specifically, the radar digital signal processor 12 
extracts target information from a continuous wave linear frequency 
modulated waveform and the processor 12 implements two major processing 
procedures. The target detection procedure 26 provides for target 
detection within each FM phase of the frequency modulation ranging (FMR) 
waveform. After detection, the target resolving procedure 30 of the 
present invention associates and resolves range and doppler signals for 
each detected target provided by the target detection procedure 26 from a 
set of detections observed for each phase (slope segment) of the frequency 
modulated ranging waveform. This target detection procedure 30 is at the 
heart of the present invention. 
The multislope frequency modulated ranging target resolving procedure 30 is 
comprised of a centroiding procedure 31, an association procedure 32 using 
a maximum likelihood estimator, an elimination procedure 33 to minimize 
the number of ghosts, and a velocity and range computation procedure 34. 
These procedures are discussed in detail below. The inputs for the 
frequency modulation ranging target resolving procedure 30 are the outputs 
of the magnitude and thresholding prodcedure 26 for each of the FMR phases 
(N phases). The output of the target resolving procedure 30 is the target 
range and range rate set (velocity) for each of the targets in a range and 
doppler region of interest. 
The range and range rate data output of the target resolving procedure 30 
may be employed as an input to an adaptive cruise control system 40 or to 
a tracker 50 employed in an airborne radar tracking and missile guidance 
system, for example. In the cruise control system 40 the range and range 
rate data may be used to cause an airbag to deploy, or to cause vehicle 
breaking action through anti-lock brake controls, or to provide collision 
warning signals to the operator of the vehicle. In the airborne radar 
system, the tracker 50 uses the range and range rate data to more 
accurately track potential targets, when compared to tracking systems 
employing conventional target resolving procedures. 
In addition to resolving the target, the target resolving procedure 30 also 
may be adapted to reject undesired aliased long-range targets and process 
only target regions of interest (to reduce signal processing throughput 
requirements) such as a nearest target, for example. Furthermore, when a K 
out of N detection rule is employed in the target resolving procedure 30, 
it provides the capability of detecting targets that compete with mainlobe 
rain clutter, mainlobe ground clutter, and leakage in the receiver 23. The 
K out of N detection rule is employed in situations where the above-cited 
noise conditions are present. 
The centroiding procedure 31 produces the target position within a filter 
of the doppler filter 25 and provides a means for handling extended and 
overlapped targets as will be described below. The centroiding procedure 
31 groups target returns of adjacent filters for each phase to form 
discriminants that estimate target position and extent as follows: 
##EQU1## 
In the above equations, P.sub.f is the signal power at frequency f, and the 
indices f.sub.min to f.sub.max specify a group of adjacent filters to be 
centroided. The target extent (EXT) discriminant measures the frequency 
spread that is used for target discrimination. With reference to FIG. 2, 
the adjacent detected filters are grouped together from a local minimum to 
another local minimum. FIG. 2 shows the filter grouping employed in the 
target resolving procedure 30 of FIG. 1. Consequently, if adjacent 
detected filters have N local peaks, there are N groups that are 
centroided, as is shown in FIG. 2. 
The centroid provides an accurate target position that enhances the target 
association performance of the association procedure 32 by reducing 
ghosts. The target extent discriminant is utilized to break up adjoining 
hits resulting from extended or multiple overlapping targets. This is 
required in automobile applications, for example, because there is a 
higher probability of observing large extended targets, such as trucks. 
Breaking up targets reduces the possibility of losing targets at the risk 
of increasing the probability of creating a ghost when target filters 
overlap. The extent logic of the centroiding procedure 31 is also 
dependant upon the number of contiguous filters. The centroiding procedure 
31, as part of the overall FMR resolving procedure 30, is the most 
significant from a performance point of view. 
The association procedure 32 groups the detection from each phase by 
expecting hits to be within a gate size of projected feasible target 
doppler filter location. The projected doppler filter location and the 
gate size depend on all previous FMR phase observations. The association 
procedure 32 uses the desired range information for initialization, then 
uses a maximum likelihood estimator to predict the filter position for the 
next phase. 
First, the association procedure 32 associates the detected target filters 
from two phases with slopes having the same sign. The gate size for the 
first association is established by the desired minimum and the maximum 
target ranges. This minimizes the number of potential associations in 
these two phases and also eliminates all targets at ranges longer than the 
maximum range. By properly selecting the slope values (the same sign slope 
is prime to each other), long range rejection can be much larger (10 
times) than the maximum range from the waveform. If the system 10 is 
tailored to provide the nearest target or targets ordered by their 
distance, then the system 10 is adapted to sort the list of possible 
associated targets having two same sign slopes. This first step of the 
association procedure 32 and the selection of the FMR slope values 
determines the signal processing requirement of the system 10. 
With the measurements from the first two slope associations, a maximum 
likelihood estimator is used to predict the position of the phase return 
as follows: 
##EQU2## 
where f.sub.est.sup.(N+1) is the position of the phase return, .omega. is 
the average of the target return, .omega..sub.i is the value of target 
returns for slope i, .rho. is is the average of the correlation between 
the slope value and the target return, N is the number of slopes used, 
s.sub.i is the value of the slope i, s.sub.i.sup.2 is the square of the 
slope value, E.sub.N (s.sup.2) is the second moment of the slope value, 
E.sub.N (s) is the mean of the slope value, .sigma..sub.s.sup.2 (N) is is 
the variance of the slope value, and s.sub.N+1 is the slope value of the 
next phase. 
If N=2, s.sub.i is the i.sup.th phase slope and .omega..sub.i is the 
frequency measurement for a target hit in the i.sup.th phase. The variance 
of the estimator to set a gate for which the phase 3 return is in the gate 
with very high probability (for example a three-sigma gate) is: 
##EQU3## 
where .sup..sigma. M.sup.2 is the variance of the measurement. 
If there is an association in phase 3, for example, it will repeat the 
above step for all the following phase returns (phase number 4 to phase 
number N) as shown in FIG. 3 (shown for a four FMR-slope system). More 
specifically, FIG. 3 shows the association procedure 32 employed in the 
target resolving procedure 30 of FIG. 1. 
The above association procedure 32 is for an N out of N detection rule. A 
similar procedure may applied for a K out of N detection rule. The K out 
of N detection rule may be used to provide target detection when the 
target return is predicted to fall in the region for which it has to 
compete with receiver leakage, mainlobe clutter, or mainlobe rain clutter 
in some of the FMR phases. In this instance, the association procedure 32 
skips the phases in which it predicts the target return will be masked by 
an interference signal. 
The elimination procedure 33 reduces the number of candidate targets that 
correlate in four FMR phases by grouping all paths with three common hits. 
The chosen target out of each group is the one with the minimum estimation 
error. The elimination procedure 33 optimizes performance by greatly 
reducing the number of ghosts while only slightly decreasing the target 
detection probability. Since the discriminant function partitions an 
extended target into individual targets, the elimination procedure 32 
groups these parts back into a single target. This is done by grouping 
targets with the same doppler and a range difference of less than a 
specified length, such as the length of a car, for example. 
The range (R) and velocity (R) computation procedure 34 provides the target 
range (R.sub.est) and velocity (R.sub.est) estimates using the following 
formulas: 
##EQU4## 
where c is the speed of light, .lambda. is the wavelength, and N is equal 
to the number of associated slopes. The outputs of the range and velocity 
computation procedure 34 are the target range and velocity for each 
target. 
The above described invention has been reduced to practice in the form a 
non-scanning 60-GHz radar and two scanning 60-GHz radars for automobile 
cruise control applications. The purpose of the non-scanning radar is to 
show the ability of the radar system 10 operating in complex road 
scenarios. Tests show that the radar system 10 accurately provides range 
and range rate measurement of the same target in multiple-target 
situations. The radar system 10 demonstrates the ability of rejecting 
large but distant targets by using its waveform processing. The tests show 
that the centroid procedure 31 effectively discriminates two close 
targets. Adaptive cruise control system testing demonstrates the 
performance of the adaptive cruise control system in highway road 
conditions. The ability to simultaneously measure range and range rate 
(velocity) significantly enhances the performance of the present system 10 
in automobile cut-in situations. 
Thus there has been described new and improved maximum likelihood 
estimation and range only initialization methods for use in multislope 
linear frequency modulated waveform radar systems. Production of adaptive 
cruise control systems and collision warning system are made possible by 
the present invention. Improved airborne radar systems may be made using 
the present invention to provide more accurate range and range rate 
measurements than current frequency modulated waveform processing 
techniques having the same signal bandwidth. 
It is to be understood that the above-described embodiment is merely 
illustrative of one of the many specific embodiments which represent 
applications of the principles of the present invention. Clearly, numerous 
and other arrangements can be readily devised by those skilled in the art 
without departing from the scope of the invention.