Sound Exposure Calculations for Transient Events and Other

Improvements to an Acoustical Tactical Decision Aid

ARL-TR-2757 August 2002

D. Keith Wilson, V. Anh Nguyen, Nassy Srour, and John Noble

Approved for public release; distribution unlimited.
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Destroy this report when it is no longer needed. Do not return it to

the originator.
ARL-TR-2757 August 2002

Army Research Laboratory

Adelphi, MD 20783-1197

Sound Exposure Calculations for Transient Events and Other

Improvements to an Acoustical Tactical Decision Aid

D. Keith Wilson, John Noble

Computational and Information Sciences Directorate

V. Anh Nguyen, Nassy Srour

Sensors and Electron Devices Directorate

National Ground Intelligence Center

220 Seventh Street NE

Charlottesville, VA 22902-5396

Sponsored by

Approved for public release; distribution unlimited.
Abstract

Recent enhancements to an acoustical tactical decision aid, called the

Acoustic Battlefield Aid (ABFA), are described. ABFA predicts the effects

of the atmosphere and local terrain on the performance of acoustical

sensors, using advanced sound propagation models. Among the

enhancements are (1) sound-exposure and detection calculations for

moving and transient sources, (2) new display capabilities including

loading of vector-map features from CDs, (3) an interactive menu for

entering and managing acoustical and meteorological ground properties,

(4) initialization of runs from field trials stored in the U.S. Army Research

Laboratory’s Automatic Target Recognition Acoustic Database, (5) a

Java-based interface to numerical weather forecast data over the Internet,

and (6) creation of a Windows executable version using the Matlab

compiler.

ii
Contents

1 Introduction 1

2 Display Enhancements 2

2.1 Display Formats and Options . . . . . . . . . . . . . . . . . . 2

2.2 Display Rotation . . . . . . . . . . . . . . . . . . . . . . . . . 3

2.3 Positioning of the Calculation Domain . . . . . . . . . . . . . 4

2.4 Map Backgrounds from Vector Format Geographic Data . . . 4

3 Initialization from the ATR Database 7

4 Spectral Representations 11

5 Moving and Transient Sources 14

5.1 Internal Representation of Nonstationary Sources . . . . . . . 14

5.2 Calculation Method for Nonstationary Sources . . . . . . . . 15

5.3 Moving Source Implementation . . . . . . . . . . . . . . . . . 17

5.4 Transient Source Implementation . . . . . . . . . . . . . . . . 18

6 Java Weather Interface 23

7 Dependence of Sound Speed on Atmospheric Humidity 25

8 Ground Parameter Menu 29

9 Creation of an ABFA Windows Executable 31

10 Concluding Remarks and Future Recommendations 33

iii
Figures

1 Map for the Annapolis, MD area generated from VMAP0

vector features and DTED terrain elevations. . . . . . . . . . 6

2 ABFA display after initialization from ATR Acoustic Database

file apg8 36. The path of a ground vehicle driving on Spesutie

Island (APG, MD) is shown. The starting point of the path is

indicated by an x and the ending point by an arrow. Positions

of acoustic sensors are indicated by circles. . . . . . . . . . . . 9

3 ABFA display after initialization from ATR Acoustic Database

file apg8 66. The path of a helicopter flying over the Aberdeen, MD area is shown. See Figure 2 for legend. . . . . . . 10

4 Probability of detection display for a moving source. White

represents high probability of detection; medium gray represents near-zero probability of detection. . . . . . . . . . . . . 19

5 Three representations for shock waves and explosions. Plotted

is p (t) /A, where A is the peak overpressure. The time axis is

normalized by the positive phase duration Tp. . . . . . . . . . 20

6 Ground parameter menu. . . . . . . . . . . . . . . . . . . . . 30

iv
1. Introduction

The Acoustic Battlefield Aid (ABFA) is a tactical decision aid providing

the capability to predict and simulate performance of battlefield acoustical

sensors. It can also be used to predict noise impacts from military

activities. ABFA combines advanced models for sound propagation in the

atmosphere with a library of source representations and algorithms for

assessing sensor performance. Important propagation effects, such as

refraction by atmospheric wind and temperature gradients, signal

coherence reduction from atmospheric turbulence, and shadowing by

terrain features and buildings, are included in the calculations. Early

versions of ABFA were described in two technical reports. The first (Wilson

1998) described the basic organization and physical models used by the

program. The second (Wilson and Szeto 2000) described the user interface,

object representations, and some tools designed to enhance functionality.

The present technical report describes several recent enhancements to

ABFA that are part of the new Version 3.0. These features include the

ability to perform calculations with transient and moving sources, access

to various sources of weather data over the Internet, map displays with

geographic features from CD-ROMs produced by the National Imagery

and Mapping Agency (NIMA), and an informative ground parameter

display allowing users to create and name their own ground types. The

report also describes how a Windows executable version of ABFA was

created from its Matlab (The MathWorks, Inc. 2000) source code using

the Matlab compiler and function libraries.

One of the most significant enhancements in ABFA Version 3.0 is the

ability to simulate the performance user-supplied detection and

beamforming algorithms. A separate technical report by Wilson et

al. (2002) describes this new capability.

1
2. Display Enhancements

Many graphical enhancements are present in the new version of ABFA.

Three basic types of displays are now available along with options for

customizing them. Rotation of the display is easily done with the mouse,

and convenient new tools for positioning the computational domain have

been developed.

2.1 Display Formats and Options

Previous versions of ABFA (specifically Versions 2.5 and 2.6) allowed two

primary types of displays: a color image representing the calculation values

(or terrain elevations) could be overlaid on either a 3-D mesh plot or a 2-D

georectified, pixelized map background (.jpeg or .gif format). The new

version of ABFA, 3.0, adds a third type of display, in which the user

creates his/her own map background using vectorized map features found

on CD-ROMs produced by NIMA. This type of display is discussed in

more detail later.

Although the appearance of the three of the primary display types may

seem very different, they are all created in a similar manner. Technically,

each display type consists of a color surface plot above a layer of

miscellaneous objects whose characteristics are customized by the user.

Matlab’s FaceAlpha (transparency) property of the surface plot and the

EraseMode property of the underlying miscellaneous objects are changed

to achieve the desired displays. For example, to create the 3-D mesh plot,

the surface’s FaceAlpha is normally set to 1, which produces an opaque

plot. The view angle is set from the side to create the 3-D appearance. To

create an overlay on a map background, the surface’s FaceAlpha value is

set to 0.5, which creates a semi-transparent plot. The surface mesh lines

are erased and the map background is placed on the layer below the

surface. Setting the view angle overhead, a 2-D, map-style plot is

produced. In the vector-map feature mode, the user-selected features are

plotted on the lower layer with the EraseMode property set to “none”.

This setting allows the features to be seen even when the FaceAlpha

property of the color surface is set to 1.

Users can add grid and elevation lines from the display options dialog box,

which is accessed from the Display pull-down menu. Terrain elevations

below a user-specified elevation (set to 0 m by default) can be colored blue

2
to suggest water if desired. A contour plot of the current calculation

quantity can be also be added to the display. On the 3-D mesh plot, the

contours are visible on a flat surface underneath the mesh. These contours

are usually partially obstructed by the overlying mesh. (The display can be

rotated to see the contours more clearly.) For the map background

displays, the color surface is made partially transparent by default, so as

not to obscure the contours. To create pure contour plots, the overlying

surface may be made invisible from the display options dialog box by

selecting “Make color display image fully transparent.”

With regard to the display of geographic information, it should be noted

that the ABFA graphical display and calculations are rectilinear, thereby

being based on the flat-earth assumption. This is entirely reasonable for

the envisioned applications of the program, which involve areas of roughly

20 × 20 km or less. Although the user can choose to display and enter

coordinates in relative (easting and northing from a fixed origin at the

southwest corner of the display), UTM (Universal Transverse Mercator),

and latitude/longitude coordinate systems, the graphical display and

calculations are always based on the relative coordinates. For example, in

the latitude/longitude system, ABFA simply produces linear axes

interpolating between the latitude and longitude of the southwest and

northeast corners of the display. The display still shows relative positions

based on a flat-earth assumption; only the axes labels are changed. When

positions of an object are entered in a latitude/longitude system, ABFA

first converts the coordinates to UTM (WGS-84) coordinates. It then

subtracts the UTM coordinates of the origin (southwest corner) from the

object’s coordinates to determine the relative coordinates. The resulting

relative coordinates are subsequently used for display and calculations.

Entry of coordinates in a UTM system simply omits the first step in this

procedure. When working with UTM coordinates, ABFA determines the

grid zone based on the location of the origin.

2.2 Display Rotation

A significant change in the new version of ABFA that will be immediately

evident to users of previous versions is the removal of the slider bars

controlling the azimuth and elevation view angles. The slider bars have

been relplaced by the “Enable Display Rotation/Disable Selection”

command on the ABFA Display pull-down menu. When the user enables

rotation from the pull-down menu, or presses Ctrl-R, the display enters a

rotation mode where the view angles can be adjusted by clicking on the

terrain display with the mouse and then dragging. In the rotation mode,

the current mouse position is indicated by a “fleur” symbol (perpendicular,

3
double arrows). A 3-D outline box, indicating the extent of the terrain

mesh, is displayed during the dragging process. The numerical values of

the azimuth and elevation appear in the lower left corner of the window.

When the view angles have been set as desired, the user should select

“Disable Display Rotation/Enable Selection” from the Display pull-down

menu or press Ctrl-R. This returns ABFA to the source/receiver selection

mode, where a mouse click on a source or receiver selects it for a

calculation. In the selection mode, the mouse position is indicated by a

standard pointing arrow.

2.3 Positioning of the Calculation Domain

Several methods for positioning the computational domain can be accessed

from the Terrain pull-down menu. The first of these (which was the only

one available in previous versions), involves specifying the

latitude/longitude or UTM coordinates of the southwest and northeast

corners the domain. An alternative method now available is for the user to

first specify the locations of sources and/or receivers of interest, and then

have ABFA automatically choose the southwest and northeast corners of

the domain so that all sources and receivers are visible with a suitable

margin around the edge of the display. In addition, the Digital Chart of the

World’s (DCW’s) Gazetteer can be searched for place names. (The DCW

Gazetteer contains more than 100,000 place names, with an emphasis on

names of cities and major airports. It is distributed with ABFA, so that

users need not obtain their own CD-ROM.) To use this capability, the user

specifies a search string. All matches found in the DCW Gazetteer are then

listed. Once the user has selected the desired match from the list, ABFA

retrieves the latitude/longitude coordinates from the Gazetteer and then

centers the computational domain on this location.

Once the calculation domain has been set, the user can zoom in/out and

reposition the center of the display by selecting “Zoom In/Out and

Translate Domain” from the Terrain pull-down menu. The user specifies

values for the zoom factors and translations in km for the easterly and

northerly coordinates. If the display includes terrain elevations [from

Digital Terrain Elevation Data (DTED) CDs provided by NIMA] and

vector map features, the user is prompted to insert the CDs so ABFA can

load geographic data for the new display location.

2.4 Map Backgrounds from Vector Format Geographic Data

As mentioned earlier, the new version of ABFA can display geographic

objects found on NIMA CDs. Both the Vector Map Level 0 (VMAP0)

4
format and its predecessor, DCW, are supported through functions found

in the Matlab Mapping Toolbox. These CDs contain features in several

different themes, including political boundaries, population centers, roads,

railways, airports, rivers, lakes, and coastlines. ABFA users can exercise

control over which of these themes are displayed from the “Show

Geographic Objects” dialog box accessed through the Display pull-down

menu.

ABFA internally sets the colors to use for the various map features:

• Rivers are plotted as thin, medium blue lines.

• Coastal boundaries are plotted as thick, medium blue lines.

• Roads and railways are plotted as thin, black lines.

• Airports are plotted as open black squares.

• Political boundaries are plotted as thick, white lines.

• The outlines of population centers are plotted as medium width, gray

lines.

An example vector-feature map background for the Annapolis, MD area is

shown in Figure 1. A 20 × 20 km region is shown. This map was generated

from the NIMA VMAP0 and DTED level 1 CDs. The city limits for

Annapolis are indicated by gray lines near the center of the map. The

Chesapeake Bay is to the east. Major roadways, including part of the Bay

Bridge, are indicated as solid lines. Locations of surface weather stations

(which are maintained by ABFA in a separate file) appear as white

triangles. A close look at the display suggests that the outline of Annapolis

is not correctly positioned on the penninsula between the Severn and

Magothy Rivers, being shifted somewhat to the south and west. This

occurs because the VMAP0 coordinates have an accuracy of several

hundred meters and therefore do not always line up well with the more

precise DTED level 1 coverage.

When users “right-click” on the map features, a description of the feature

pops up. These descriptions, which are taken from the NIMA CDs, often

do not provide information as specific as desired. For example, U.S.

Interstate 95 would carry the generic description “Primary or secondary

roads or highways; Functional” when loaded from DCW. If desired, the

object may be renamed by clicking on the description, thereby opening a

property dialog box. The string property for the object (its name) can

then be changed. Text annotations may also be added to the map from the

Display pull-down menu. The word “Annapolis” in Figure 1 was added in

this way, because the VMAP0 CDs (unlike the DCW CDs) do not include

place names.

5
Figure 1. Map for the Annapolis, MD area generated from VMAP0 vector features and

DTED terrain elevations.

6
3. Initialization from the ATR Database

The U.S. Army Research Laboratory (ARL) has collected a large database

of acoustic signatures, primarily from trials conducted at Aberdeen

Proving Ground (APG), MD. The signatures are stored in a binary

format, together with Global Positioning System (GPS) data for the target

and sensor positions, target descriptions, sensor characteristics, weather

conditions, and a classification of the local ground type. These files have

been assembled with a set of graphical and analysis tools, together creating

the Automatic Target Recognition (ATR) Acoustic Database/Laboratory

(Nguyen et al. 1999).

A capability has been developed to initialize ABFA runs with trials from

the ATR Acoustic Database. Three types of files are used:

1. The GPS target coordinate file, titled xxxx t.gps, where “xxxx” is

the field campaign designation (e.g., apg5 for the fifth set of trials

conducted at APG) and “t” is the trial number. This file has a text

format, generally with four columns: time (24-hr clock), UTM

northing, UTM easting, and height above ground level. The height

column is sometimes omitted. Each line in the file represents the

target coordinates at a different time. Multiple vehicles may be

stored sequentially in the GPS file. Each vehicle appears as a

separate block, with blocks separated by a blank line.

2. The GPS sensor coordinate (survey) file, titled xxxx.sur. This text

file contains the UTM coordinates (northing followed by easting) for

each sensor in the field campaign. A self-contained array of

microphones is considered to be a single sensor. The coordinates of

each sensor is listed on a separate line.

3. The header file(s), titled xxxx t s.hdr. Here “s” is the sensor

number. The header files are unique for each trial and sensor,

containing the day of year, time of day, the target type(s), the array

configuration, microphone calibrations (in some cases), the weather

and ground conditions, and other information.

A run is initialized from the ATR Acoustic Database by selecting

“Configure ABFA from ATR Database Files” from the Tools pull-down

menu. ABFA first prompts for the name of the GPS target coordinate

(.gps) file. An ABFA moving source representation is then created from the

7
information in this file. Next, coordinates of the receiver(s) are loaded from

the related survey (.sur) file. ABFA then performs a search for all available

.hdr files from the trial. It loads the target type, day of year, time of day,

and weather and ground conditions from the first available file. An attempt

is made to find a close match between the target type and available target

representations in the ABFA library, although this is not always possible.

The array configurations are then loaded from each of the available .hdr

files. As for the targets, ABFA attempts to find a match between the array

configuration and the available receiver representations. The last step in

the process is to redraw the display and update the internal ABFA settings

to reflect this new information. As a part of this process, terrain elevations

and vector feature map data can be loaded if desired.

Some example ABFA initializations from the ATR Acoustic Database are

shown in Figures 2 and 3. Both of these trials were connected in the

Aberdeen, MD area on 17 December 1998. Figure 2, which is for trial

apg8 36, shows the path of a ground vehicle on Spesutie Island, APG, MD.

The initial position of the vehicle is marked by an X and the final position

by an arrow. Positions of sensors during the trial are indicated by circles.

The second Figure, 3, is the flight path of a helicopter.

In the future, the capability to initialize ABFA runs from the ATR

Acoustic Database should provide excellent opportunities for verifying

ABFA predictions.

8
Figure 2. ABFA display after initialization from ATR Acoustic Database file apg8 36. The

path of a ground vehicle driving on Spesutie Island (APG, MD) is shown. The starting

point of the path is indicated by an x and the ending point by an arrow. Positions of

acoustic sensors are indicated by circles.

9
Figure 3. ABFA display after initialization from ATR Acoustic Database file apg8 66. The

path of a helicopter flying over the Aberdeen, MD area is shown. See Figure 2 for legend.

10
4. Spectral Representations

ABFA performs its propagation calculations in the frequency domain. As

described in an earlier technical report (Wilson and Szeto 2000), the

frequency-domain representation for the acoustic sources and background

noise is composed of finite-width bands, each band having a power-law

dependence on frequency. Designating the overall power spectral density as

S (f) (where f is frequency) and the power spectral density in each band

as Sn (f), the representation can be written mathematically as

S (f) = X

N

n=1

Sn (f), (1)

where

Sn (f) = (

Anf

pn , f`,n ≤ f < fu,n

0, elsewhere.

(2)

In these equations, f`,n is the lower-frequency bound for band n, fu,n is the

upper-frequency bound, An is the spectral coefficient, and pn is the

power-law exponent. The spectral densities are assumed to be derived from

sound-pressure signals that have been normalized pref = 20 μPa, the

standard reference pressure for aeroacoustics. Therefore, the actual units of

the spectral densities are seconds.

Internally, ABFA implements the spectral representations as Matlab

structures containing four fields: LowFreq, HighFreq, SpecSlope, and

loudness. In the standard representation, these fields are each arrays with

N elements, containing the f`,n, the fu,n, the pn, and the sound-pressure

levels (SPLs) Ln. Here Ln is obtained by integrating equation (2) across

the frequency band:

Ln = 10 log Z fu,n

f`,n

Sn (f) df =







10 log hAn (pn + 1) f

pn+1

u,n − f

pn+1

`,n i , pn 6= −1

10 log [An ln (fu,n/f`,n)] , pn = −1.

(3)

The units of Ln are dB re 20 μPa.

In addition, three representations alternative to the standard one are

provided: 1/3-octave band, octave band, and Fast Fourier Transform

11
(FFT) bin coefficients. The last of these was added to ABFA Version 3 to

support calculations with transient source emissions. Internally, the

currently active representation is indicated by the field OctaveBand, which

has a value of 0 for the standard representation, 1 for 1/3-octave-band

levels, 2 for octave band levels, and −1 for FFT bin coefficients. The

various representations and conversions between them are described in the

following.

• Octave-Band Representation. Two frequencies are spaced by an

octave when the higher one is double the lower. In the ABFA

octave-band representation, the value stored in the loudness field is

the value of Ln that would be observed if the frequency limits of the

band were expanded or contracted such that this frequency doubling

condition is met. The power-law exponent pn is always −1 in the

octave-band representation. Because the SPL for pn = −1 is given by

the equation Ln = 10 log [An ln (fu,n/f`,n)], the corresponding

octave-band level would be Loct = 10 log (An ln 2). Equating the Ans,

we find

Ln = Loct + 10 log 

ln (fu,n/f`,n)

ln 2 

. (4)

• 1/3-Octave-Band Representation. This representation is the same as

for octave bands, except that the loudness field stores the value of

Ln that would be observed if the frequency limits of the band were

expanded or contracted such that the higher frequency is 21/3times

the lower. The resulting equation relating the standard level to the

1/3-octave level is

Ln = L1/3 + 10 log 

ln (fu,n/f`,n)

ln 21/3



. (5)

• FFT Bin Coefficients. The bin coefficients represent the Fourier

transform of the pressure signal recorded at a microphone,

normalized by pref. They are complex values so that the full time

series can be reconstructed. Only the first M/2 + 1 coefficients

(where M is the length of the time series) need be stored due to the

symmetry inherent to the transform of a real series. Denoting the

sampling rate as fs, the lower frequencies of the bins are

f`,n = (n − 1) (fs/M) and the upper frequencies are fu,n = n (fs/M).

The power-law exponent pn is always 0 in the bin coefficient

representation. Assuming the input signal is normalized by pref, the

FFT bin coefficients Yn are related to the sound power levels by

Ln = 20 log10 |Yn| . (6)

12
Note that the Lns can be derived uniquely from the Yns, but not

vice-versa, due to the signal phase information in the Yns.

ABFA’s Acoustic Waveform Analysis User Interface [(AWAUI), see Wilson

and Szeto (2000) ] was extended to support the FFT bin coefficient

representation. When called with the OctaveBand field set to −1, the user

may switch between displays of the time series and power spectrum. When

AWAUI is called with one of the other representations, the time series

display is disabled because it cannot be reconstructed without the signal

phase information.

13
5. Moving and Transient Sources

Previous versions of ABFA assumed that all sources produced steady

signals, or at least that received signals could be considered steady over a

signal integration (processing) time of the sensor. In signal processing

parlance, the received signal statistics were assumed to be stationary in

time. However, the received signal originating from a moving or transient

source varies in time (i.e., is nonstationary). Because ABFA performs its

calculations in the frequency-domain, it is challenging to develop

techniques to accomodate nonstationary signals that are accurate yet not

too computationally intensive.

The current version of ABFA allows the received spectrum to vary from

one moment in time to the next. The spectrum is considered to result from

repeated, short-time Fourier transforms applied at each time interval. So

long as this interval is short in comparison to the timescale over which the

changes in the received signal occur, the short-time Fourier transform

representation is a reasonable one. In this section, we describe how moving

and transient source calculations are implemented through this new

representation.

5.1 Internal Representation of Nonstationary Sources

The information on each source is stored by ABFA in a structured variable

called SourceInfo. Previous versions of ABFA included the following

among the fields in SourceInfo: xcoord, the eastward displacement of the

source relative to the southwest corner of the computational domain;

ycoord, the northward displacement of the source relative to the southwest

corner of the computational domain; and zcoord, the vertical displacement

of the source relative to the local terrain elevation. These were all scalar

values. ABFA Version 3.0 extends this representation to include the field

tcoord, which is the time relative to some convenient initiation time. The

fields xcoord, ycoord, zcoord, and tcoord can all be vectors (of the same

length M), representing 4-D coordinates of the source. If M = 1, the

source is assumed to emit a stationary (constant for all time) signal and

the value of tcoord has no effect. If M > 1, the source is assumed to turn

on at tcoord(1) and turn off at tcoord(M). The spectral loudness field

(discussed in Section 4) has been generalized to be an M × N matrix,

where N is the number of frequency bands. If the coordinate fields all have

14
length M, but the loudness field has size 1 × N, the source spectrum (but

not necessarily the receiver spectrum) is assumed to be stationary,

although the source coodinates may vary.

Much of the discussion in the previous paragraph applies to the RcvrInfo

structure as well, which contains the properties of a receiver. A tcoord

field has been added and all coordinate fields can be vectors. The extended

coordinate fields in RcvrInfo allow implementation of moving receivers

such as unmanned aerial vehicles (UAVs). However, the RcvrInfo contains

no counterpart to the loudness field. Computational implementation of

moving receivers is nearly the same as for moving sources. The main

difference is that the principle of acoustic reciprocity (Pierce 1981) is

applied (along with a reversal of the wind direction) to convert the moving

receiver problem to a moving source problem. This procedure is valid in

the presence of refraction by atmospheric wind and temperature gradients

and other complications.

5.2 Calculation Method for Nonstationary Sources

As mentioned earlier in this section, previous versions of ABFA assumed

that the sound output from the source was steady. The user had the option

of calculating the SPL produced by the source. The SPL is defined as

(Crocker 1997)

Lp = 10 log10 

p

2

rms

p

2

ref



, (7)

where prms is the root-mean-square sound pressure.

For sources that are nonstationary, one can define the sound exposure as

E =

Z t2

t1

p

2

rms (t) dt. (8)

The integration limits t1 and t2 are normally set to −∞ and ∞,

respectively. The sound exposure level (SEL) is then defined as (Pierce

1981)

LE = 10 log10 

E

p

2

refTref 

, (9)

where Tref = 1 s is the reference time interval. Hence, for a sound source

that emits a steady sound for a 1-s interval but is otherwise quiet,

Lp = LE.

The new version of ABFA includes a capability for calculating LE. When a

user selects (clicks on) a moving or transient source, and then selects

“Sound pressure/exposure level” from the Calculation pull-down menu, the

15
SEL is automatically calculated instead of the SPL. Calculations of LE

(like Lp) may be performed with no frequency weighting, or with an A- or

C-weighting network standard in noise control applications (Krug 1997).

Users should keep in mind that ABFA’s SEL calculation includes only the

contribution from the selected source; the contribution from the noise

background is not included. If it were, the SEL would become infinite.

The SPL and SEL calculations are primarily useful in noise control

applications. In most U.S. Army tactical scenarios, however, a sensor

processes a signal for a finite time interval (the sensor integration time)

and then reaches a decision or produces a final result. The performance of

the sensor is determined by the relative exposure of the sensor to the

signal of interest (s) and the noise (n) during the integration time.

Accordingly, it is useful to define a signal exposure as

Es =

Z t1+T

t1

s

2

rms (t) dt, (10)

and a noise exposure as

En =

Z t1+T

t1

n

2

rms (t) dt, (11)

where T is the sensor integration time, and srms and nrms are the

root-mean-square sound pressures due to the source and noise,

respectively. The signal-to-noise ratio, expressed in decibels, is then

SNR = 10 log10 

Es

En



. (12)

Because the noise level is assumed to be constant (stationary),

equation (11) reduces to En = n

2

rmsT. On the other hand, it would be

impractical to implement equation (10) directly into a tactical decision aid

such as ABFA. The exact times when the sensor turns on and off would

need to be specified, and then the signal-to-noise ratio (SNR) would need

to be calculated for each individual processing interval. Most users do not

want to analyze a scenario to this level of detail. Hence, a simplified

methodology has been developed. This methodology is based on

determination of the SNR for two scenarios representing opposite extremes.

Let us illustrate the two extreme scenarios based on a moving source. In

the first scenario, the source, when it reaches the portion of its trajectory

maximizing the SNR, is moving slowly in comparison to the integration

time of the sensor. The SNR is therefore nearly constant during the

processing. It would be reasonable to approximate Es by finding the peak

16
value of s

2

rms (t) over the source trajectory and then multiplying by T,

similarly to how the noise is processed:

Es ' max s

2

rms (t)



T. (13)

In the second scenario, the source moves very rapidly past the sensor, so

that the signal level is high only for a small fraction of the integration

time. The integration limits in equation (10) become unimportant and one

could use the calculation of LE to determine Es:

Es ' p

2

refTref10LE/10

. (14)

To estimate the SNR of a processor in the presence of a moving source,

ABFA estimates Es with both of the equations above. It then calculates

the SNR using the lesser of the two estimates. This method reduces

exactly to the correct results for stationary sources and provides a very

good approximation for fast-moving sources.

Transient sources are handled similarly. The first extreme scenario would

correspond to a source signal that varies slowly over the sensor integration

time. The second extreme scenario would be a transient that starts and

finishes well within the integration time.

5.3 Moving Source Implementation

Coordinates for a moving source are loaded from text files. Text files

containing relative (in kilometers from the southwest corner of the

domain), UTM, and latitude/longitude coordinates are all supported. The

files have three required columns and an optional fourth. The first column

represents time. It can be a floating point value (which is interpreted as

having units of seconds) or any unambiguous date/time format supported

by Matlab’s datenum function. The second column is easting (for relative

or UTM coordinates) or longitude. The third column is northing (for

relative or UTM coordinates) or latitude. The optional fourth column is

the source height relative to ground level. This column will be ignored for

sources such as ground vehicles that have a fixed height. Support is also

provided for GPS coordinate files in ARL’s Acoustic Database (Nguyen et

al. 1999). These files specify UTM coordinates but have a slightly more

complicated format than the one just described.

A moving source (or receiver) is created by first following the usual

procedure for adding an object to the terrain display at a fixed location

(i.e., going to the Source menu, then to Add, then selecting the desired

type, and lastly placing it on the domain with the mouse). Next the user

right clicks on the source icon and brings up the properties dialog box. A

17
pull-down menu at the top of the dialog box displays the method by which

the coordinates are currently specified. This is initially set to “Enter fixed

coordinates and speed in boxes below.” To load a coordinate text file,

select the desired coordinate specification (relative, UTM, or

latitude/longitude) from the pull-down menu. ABFA will then prompt for

the text file name and load the coordinates. Internally, the new coordinates

are converted into relative coordinates (if necessary) and placed into the

SourceInfo structure. The loudness field is not changed, implying that

the source spectrum is stationary.

Moving sources are plotted with the source icon (usually an X) at the

initial point in the trajectory and an arrow at the termination. A line

connects the initial point to the termination. Moving receivers are plotted

in the same way, except that the receiver icon (usually a circle) is used at

the initial point.

The time steps in the source coordinate specification should be short

enough that the received signal energy does not dramatically change from

one time step to the next. If the time resolution is not fine enough, there

may be no time step close to the location at which the received signal

energy is maximized (typically near the point of closest approach to the

sensor). ABFA’s calculations of max s

2

rms (t)



in equation (13) and LE in

equation (14) will then both be poor, resulting in a poor approximation for

the SNR.

An example probability of detection calculation on a moving tracked,

armored vehicle is shown in Figure 4. The vehicle track and weather

conditions were loaded from an ATR Database trial conducted shortly

after midnight on 17 December 1998 at Spesutie Island, APG, MD.

(Terrain elevations for this trial are plotted in Figure 2.) In this trial, there

was a strong wind of 9.25 m/s blowing from the northeast. According to

the ABFA predictions, high wind noise and upward refraction over the

water confined the area of detection primarily to the island.

5.4 Transient Source Implementation

Three basic transient signal models (plotted in Figure 5) are presently

available.

• N-wave. The N-wave represents shocks generated by supersonic

aircraft and other sources. It is described internally by the following

equation for the sound pressure:

p (t) = (

A (1 − t/Tp), 0 ≤ t ≤ 2Tp,

0, elsewhere,

(15)

18
Figure 4. Probability of detection display for a moving source. White represents high

probability of detection; medium gray represents near-zero probability of detection.

19
Figure 5. Three representations for shock waves and explosions. Plotted is p (t) /A, where

A is the peak overpressure. The time axis is normalized by the positive phase duration

Tp.

20
where A is the peak overpressure and Tp is the positive phase

duration.

• Exponentially decaying explosion. Explosions have often been

modeled previously using an exponentially decaying function,

described by the following equation:

p (t) = (

A (1 − t/Tp) exp (−t/Tp), 0 ≤ t,

0, elsewhere.

(16)

Internally, ABFA cuts off the pressure signal at t = 8Tp, setting it

equal to zero thereafter. At this time, the pressure has decayed to

−0.0023A, down from its initial value of A.

• Reed (1977) explosion model. Reed (1977) points out that the

exponential model poorly describes the negative pressure phase of an

explosion and offers the following equation as an alternative:

p (t) = (

A (1 − t/Tp) (1 − t/Td)



1 − t

2/T2

d



, 0 ≤ t ≤ Td,

0, elsewhere,

(17)

where Td is the total pulse duration. To produce a net zero-mean

flow condition, Td is set to Tp/0.28 (White 1991).

To accommodate transient signals, a new field was added to the

SourceInfo called “OtherParam”. This field is a Matlab cell array, whose

first element is a string representing the implementing function for the

transient (Nwave, ExpExplode, or Reed1977, for the three currently

available signal models). The remaining elements of the cell array are

arranged in pairs, the first element being a descriptive string for the

parameter needed by the implementing function and the second its default

value. These additional parameters are listed when the source properties

dialog box is opened, and they are sent in order to the implementing

function.

The internal coordinate representation of a transient source is initially the

same as a source with fixed spatial coordinates, with the fields tcoord,

xcoord, ycoord, and zcoord of the SourceInfo structure all being scalar

values. However, the spectral representation (the loudness field in

SourceInfo) is in the FFT bin coefficient format as indicated with a value

of −1 for the OctaveBand field, as described in Section 4. When a

calculation is started, ABFA converts the SourceInfo to a representation

similar to that of a moving source. The conversion process is driven by the

sensor’s signal integration time. If the integration time is larger than the

length of the transient, then the spectrum of the transient is passed

21
without alteration. In this case, equation (14) will be used to determine

the SNR. If the integration time is shorter than the length of the transient,

the transient will be divided into M blocks having (as closely as possible)

the same duration as the sensor integration time. The spectrum of each of

these blocks is then put into an M × N loudness field, and the coordinate

arrays of SourceInfo are expanded into M-element vectors. The spatial

coordinates are repeated, although tcoord steps forward in increments of

the sensor integration time. Generally equation (13) will be selected to

calculate the SNR.

This approach to calculations with transients may not be satisfactory if

there are strong multipaths whose separation in time is longer than the

receiver’s integration time. But in situations where the system performance

is dominated by a single propagation path or closely spaced multipaths, it

is a very reasonable approach. When performing calculations on transient

signals, the minimum frequency in ABFA’s propagation table should be set

to a very low value (e.g., 1 Hz). This is because transients often contain

strong signal energy down to very low frequencies. If the minimum

frequency in the propagation table is not low enough, extensive

extrapolation of the table will occur. This could result in very poor

transmission loss predictions.

ABFA’s AWAUI (Wilson and Szeto 2000) was modified to plot transient

signals. When AWAUI is invoked to analyze sound recordings (through the

wizards for creating new source and background noise types), it provides

the option of saving the spectrum in the FFT bin coefficient format so that

calculations can be later performed on the transient signal.

22
6. Java Weather Interface

Matlab Versions 6.0 and 6.1 support embedded Java commands. ABFA

uses this capability to provide users with access to several Internet sources

of weather data, by sending sequences of FTP and HTML instructions.

The Web sites are:

• National Weather Service Internet Weather Source (IWS),

¡http://weather.noaa.gov/weather/metar.shtml¿. This site contains

worldwide METAR (Aviation Routine Weather Report) messages

updated at hourly intervals. These messages are highly condensed

text files containing information such as surface wind speed and

direction, surface temperature, surface relative humidity, and cloud

cover. They are accessed in ABFA by entering the four-letter ICAO

(International Civil Aviation Organization) code of the weather

station of interest. Alternatively, ABFA will search a list of available

stations to find the ones closest to the current computational domain

and then prompt the user to select the station of interest. After

downloading and parsing the METAR message, a surface-energy

balance model (Wilson and Szeto 2000) is then invoked to determine

the near-ground vertical profiles of wind, temperature, and humidity,

as well as turbulence parameters used to calculate sound-field

saturation and coherence.

• National Oceanic and Atmospheric Administration Realtime

Environmental Applications Display sYstem (READY),

¡http://www.arl.noaa.gov/ready/cmet.html¿. Numerical weather

forecasts from a large number of atmospheric models are collected at

this site. ABFA currently provides access to data from the

Medium-Range Forecast (MRF) model, which covers the northern

hemisphere, and from the lower resolution Aviation (AVN) model,

which covers the entire globe. (Several other forecast models are

available at this Web site, and access to these could be added in the

future.) Access to the MRF and AVN models works in the same way:

ABFA first requests the forecast data for the latitude and longitude

of the origin (southwest corner) of the current computational

domain. The READY Web site then interpolates the

coarse-resolution forecast model data to this particular location. The

resulting vertical profiles of wind, temperature, and humidity are

23
then pushed to ABFA. Generally, these profiles do not have sufficient

resolution to accurately predict sound refraction near the ground.

Therefore, ABFA provides an option of invoking Monin-Obukhov

similarity to estimate profiles at a higher resolution within the

atmospheric surface layer, based on the values of the forecast profiles

at the lowermost two grid levels.

• National Oceanic and Atmospheric Administration (NOAA) Forecast

Systems Laboratory (FSL) Web Site,

¡http://maps.fsl.noaa.gov/newmain.html¿. Access is provided to the

RUC (Rapid Update Cycle) and MAPS (Mesoscale Atmospheric

Prediction System). These forecasts cover the United States at 20–40

km resolution. Forecasts out to 24 hrs in advance are updated every

3 hrs. ABFA also accesses the radiosonde soundings collected at this

Web site. Soundings from major airports are available, being

accessed by their four-letter ICAO code. The process of retrieving

the profiles for any of these data resources is similar to the READY

Web site retrieval. The option estimating the profiles at higher

resolution in the atmospheric surface layer using Monin-Obukhov

similarity is also provided.

In addition, ABFA can load data stored on the local computer in several

text-file formats. Supported formats currently include: METAR messages,

the ARL SCAFFIP (SCAnning Fast FIeld Program) format, the Army

IMETS (Integrated METeorological System) UAMET format, and the

Navy standard upper-air sounding format. Processing of the locally stored

METAR messages is done in the same manner as when they are

downloaded over the Internet. The SCAFFIP, UAMETS, and Navy

formats, being full vertical profiles, are processed in the same way as the

NOAA/READY and NOAA/FSL forecast data.

24
7. Dependence of Sound Speed on Atmospheric Humidity

Water vapor in the atmosphere affects sound waves in two primary ways: it

alters the attenuation (dissipation as heat) of propagating sound energy

and modifies the refractive characteristics of the air through the

dependence of the sound speed on air density. The former effect was

accounted for in earlier versions of ABFA. Users specified a single value of

the relative humidity that was subsequently used by the program to

calculate the attenuation coefficient. In the new version, the full vertical

profile of humidity is stored in the same manner as the temperature and

wind profiles for subsequent calculation of both the attenuation and sound

speed. As a result, the height-dependence of absorption and refraction by

humidity gradients are now included in calculations.

Several derivations of the dependence of sound speed on temperature and

humidity can be found in the literature, many of which contain errors or

values of constants that are inaccurate. Here a concise derivation is

presented that leads to the correct dependence of the sound speed on

humidity. It is based on the derivation in Pierce (1981).

For an ideal gas, it is well known that

c =

p

γRT . (18)

Here, γ = Cp/Cv is the specific heat ratio, R = R0/M, where R0 = 8314

m2s

−2 K−1

is the universal gas constant and M is the average molecular

mass. Note that for an ideal gas, the speed of sound is independent of

pressure. Air is a mixture consisting primarily of diatomic nitrogen,

diatomic oxygen, monatomic argon, and water vapor. The amount of water

vapor is highly variable, whereas the proportions of the other constituents

are nearly constant. The average molecular mass of moist air, weighted by

fraction, is simply

M = (1 − h) Md + hMw, (19)

where the subscript d indicates dry air, w indicates water vapor, and h is

the fraction of molecules that are water vapor. The molecular mass of dry

air is Md = 28.96, whereas the molecular mass of water vapor Mw is 18.02.∗

The specific heat ratio can be deduced from the structure of the constituent

molecules. According to the kinetic theory of gases, Cv = (R/2) (T + F),

∗Values for molecular masses in this section are taken from Table 1 in Zuckerwar (1997).

25
where T is the number of translational degrees of freedom of the molecule

(always 3) and F is the number of rotational degrees of freedom Zuckerwar

(1997). The relationship Cp = Cv + R then yields γ = (5 + F) / (3 + F).

Water molecules have an additional rotational degree of freedom in

comparison to diatomic molecules so that F = 2 + h in the mixture, and

γ =

5 + 2 (1 − h) + 3h

3 + 2 (1 − h) + 3h

=

7 + h

5 + h

. (20)

In deriving this result, the contribution of argon and other trace

constituents in the air has been neglected.

The range of values for h in the atmosphere is about 0 to 0.04 Wallace and

Hobbs (1977). Since h  1, it is reasonable to expand equations (19) and

(20) in powers of h and neglect terms of order h

2 and higher, resulting in

R = Rd [1 + (1 − ε) h] , γ = γd



1 −

2h

35 

, (21)

where ε = Mw/Md = 0.6222. Now, by substitution into equation 18, we

have for moist air

c =

p

γdRdT [1 + (33/35 − ε) h] ' 20.05√T(1 + 0.160h). (22)

Therefore, the presence of water vapor increases the gas constant but

decreases the specific heat. The effect of the vapor on the gas constant is

more significant, causing the sound speed to increase.

The molecular-fraction humidity h, while convenient for describing the

dependence of sound speed on water vapor, is not often used by

atmospheric scientists. Internally ABFA quantifies the humidity with the

specific humidity (q), defined as the mass of water vapor divided by the

total mass of air in a sample. The specific humidity relates to h as follows:

q =

hMw

hMw + (1 − h) Md

=

εh

1 + (ε − 1) h

. (23)

With h  1, this relationship implies that q is approximated by εh to first

order in h. Hence, equation (22), in terms of the specific humidity, becomes

c =

p

γdRdT (1 + ηq) ' 20.05√T(1 + ηq/2), (24)

where

η =

33

35ε

− 1 = 0.515. (25)

The second result in equation (24) follows from a Taylor series expansion

to first order in q. Frequently in practice, the relative humidity is specified

26
instead of specific humidity. Therefore ABFA includes routines to convert

between these two humidity measures. The conversion is based on the

well-known Goff-Gratsch equation (Goff 1965).

Because q  1, the contribution of humidity to the actual sound speed is

usually small. But this does not necessarily mean that the effect of

humidity is unimportant for propagation in general. Many propagation

phenomena, such as refraction and scattering, depend on contrasts between

the sound speed at different locations in the atmosphere. Therefore, it is

the deviations of the temperature and humidity from some background

state that are important. Let us write T = T0 + T

0 and q = q0 + q0

, where

T0 and q0 are reference values for the temperature and humidity (for

example the means at a fixed height), and T

0 and q0 are presumed small

perturbations. Substituting these expansions into equation (24) yields

c = c0

s

1 +

T0

T0

 1 +

ηq0

1 + ηq0



, (26)

where

c0 =

p

γaRaT0 (1 + ηq0). (27)

Keeping only the first-order contributions in T

0

, q

0

, and q0, one has

c = c0 + c

0

, where

c

0 '

c0

2



T

0

T0

+ ηq0



. (28)

Based on equation (28), with the reference values T0 and q0 taken to be

independent of height, the vertical gradient is

∂c

∂z =

∂c0

∂z =

c0

2



1

T0

∂T0

∂z + η

∂q0

∂z 

. (29)

When Monin-Obukhov similarity (e.g., Stull 1988) is invoked to model the

vertical sound-speed profile (i.e., when the user does not specify the

temperature and humidity profiles directly), the following equation applies

to the vertical gradient

∂c

∂z = −

Γdc0

2T0

+

Ptc∗

k

φh



z

Lo



, (30)

where Γd = 0.0098 ◦K/m is the dry adiabatic lapse rate (accounting for the

decrease of temperature with height due to compression in the air column),

k = 0.40 is von K ́arm ́an’s constant, Pt = 0.95 is the turbulent Prandtl

number, φh is a presumed universal gradient function, and Lo is Obukhov’s

27
lengthscale, which is described in texts on boundary-layer meteorology such

as Stull (1988). The quantity c∗ is a sound-speed fluctuation scale, given by

c∗ =

c0

2



T∗

T0

+ ηq∗



, (31)

where T∗ = − hw

0T0

i

s

/u∗ and q∗ = − hw

0

q

0

i

s

/u∗, with u∗ being the friction

velocity and hw

0

ξ

0

i

s

the vertical kinematic flux of the quantity ξ at the

surface. The following form for the profile function φh, based on results in

H ̈ogstr ̈om (1996) and Wilson (2001), is used by ABFA:

φh (ζ) = (

(1 + 7.9|ζ|

2/3

)

−1/2

, ζ < 0

1 + 8.4ζ, ζ ≥ 0

, (32)

In writing equation (30), it was assumed that the potential temperature

and humidity gradients are both proportional to φh. Integrating

equation (30), the result is

c (z) = c (zr) −

Γdc0z

2T0

+

Ptc∗

k



ln z

zr

− Ψh



z

Lo



+ Ψh



zr

Lo

 , (33)

where zr is a reference height at which the temperature and humidity are

known (typically 2 m), and

Ψh (ζ) = (

2 ln 1 + (1 + 7.9|ζ|

2/3

)

1/2



/2



, ζ < 0

−8.4ζ, ζ ≥ 0

. (34)

28
8. Ground Parameter Menu

A new ground parameter menu (Figure 6) was designed to provide

immediate feedback to users as the parameters are changed. The ground

parameters are separated into three classes: acoustical properties, radiative

properties, and aerodynamics properties.

The acoustial properties (flow resistivity, porosity, tortuosity, and pore

shape factor) determine the ground impedance and complex wavenumber

used by the propagation models. Calculation of these quantities is based

on a viscous and thermal relaxational model (Wilson 1997). When the

acoustical properties are changed, plots of the reflection coefficient and

surface impedance (normalized by the product of the sound speed and

density of air) are automatically updated.

The radiative properties (surface albedo and Bowen ratio) are used

internally by a surface-energy balance model (Wilson and Szeto 2000) to

determine the fluxes of sensible and latent heat at the ground. The fluxes

are needed to calculate the temperature and humidity profiles near the

ground, unless these profiles are specified directly by the user. When the

Bowen ratio (ratio of the sensible to the latent heat flux) is changed, a

graphical display of the flux partioning (shown in the upper middle of

Figure 6) is automatically updated. Because the flux partitioning schemes

differ at day and night, a pair of radio buttons are supplied that allow the

user to toggle between the two schemes. The surface albedo (fraction of

incoming shortwave solar radiation that is reflected by the ground) has no

effect on the flux partitioning plot, although it does affect the temperature

profile.

The aerodynamic properties (roughness and displacement heights)

primarily affect the wind profile near the ground. A display of the wind

profile, as it would in neutral atmospheric conditions, is updated when the

user changes these properties. This display is determined from the

following logarithmic form for the vertical wind profile, which is valid in

neutral conditions (e.g., Stull 1988):

U (z) = u∗

0.4z

ln 

z − d

z0



, (35)

where u∗ is the friction velocity, z0 is the surface roughness, and d is the

displacement height. Therefore, the ratio of U (z) to its value at some

29
normalization height zn is

U (z)

U (zn)

=

ln [(z − d) /z0]

ln [(zn − d) /z0]

, (36)

which is independent of u∗. As the user changes the values of z0 and d, the

plot of the ratio U (z) /U (zn) on the right side of the display is updated.

The value of zn is internally set by the program to produce a good plot.

Note that ABFA does not generally use neutral conditions in its

calculations; the purpose of the wind-profile plot in the ground parameter

menu is simply to provide informative feedback to the users as they change

the aerodynamic properties. The actual wind profile to be used in

calculations can be plotted from the Weather pull-down menu.

Figure 6. Ground parameter menu.

The name of the current ground type is shown on a pull-down list near the

bottom of the ground parameters menu. The ground type can be changed

simply by selecting a new name from the list. The parameter values are

then updated. Whenever a user changes any of the ground parameters

manually, the ground type name becomes “custom” and the “Save As”

button is activated. By clicking on “Save As,” the modified ground

parameters can be saved under a new name. This name will subsequently

appear on the ground type pull-down list. Existing ground types can be

deleted by selecting them from the pull-down list and then clicking the

“Delete” key.

30
9. Creation of an ABFA Windows Executable

One of the limitations of the ABFA code in Versions 2.5 and prior was that

Matlab was required to run it. A Matlab license with the signal

processing and mapping toolboxes costs several thousand dollars.

Therefore, it is highly desirable to find a way to distribute the code that

will not require users to obtain Matlab. Fortunately, in recent years The

MathWorks, Inc. (the developers of Matlab) has developed a compiler

that converts Matlab source code to C or C++ code (The MathWorks,

Inc. 2000). Supplementing the compiler are libraries containing object code

for Matlab graphical and mathematical functions. Most features of

interpreted (command line) Matlab are supported by the compiler and

object libraries.

We have succeeded in creating an executable version of ABFA that retains

nearly all of the functionality of the Matlab interpreted code. The only

significant difference is that the Java capability for accessing weather data

on the Internet is not supported by the compiler. Several other changes to

the original ABFA code were found necessary to produce the executable,

although these are transparent to users. The main changes were:

• Callbacks (commands that are launched from user-interface controls

such as buttons) had to be rewritten to execute from Matlab

functions rather than the Matlab interpreter command line. To

accomplish this, many of the variables that are stored in the main

workspace when ABFA runs were declared at the beginning of the

code as global variables. The callback functions then access these

global variables.

• The compiler supports only forms of the Matlab load and save

commands that explicitly provide the names of the variables being

loaded or saved. Conversion of the load and save commands in

ABFA to these forms was not difficult.

• Many ABFA functions tested for the presence of input arguments

using the Matlab exist command. However, the compiler does not

support this usage. This usage of exist was easily replaced by tests

based on the nargin variable. Similarly, in some instances ABFA

used the exist command to determine whether files were present.

This usage was replaced by an fopen command; the value returned

by fopen is examined to determine whether the file was present.

31
• The Matlab eval command, which is unsupported by the compiler,

was used by ABFA in several instances. All were easily replaced by

the Matlab feval command, which allows functions to be called

with the name of the function determined at runtime.

• As mentioned earlier, the Matlab compiler does not presently

support Java commands. Routines containing Java commands were

therefore replaced (in the compiled version of ABFA only) by

“place-holder” routines that do not include the Java functionality.

Generally speaking, the executable version of ABFA runs faster than the

interpreted Matlab code. This is particularly so for graphical processes.

The sound propagation calculations exhibit only modest speed

improvements.

32
10. Concluding Remarks and Future Recommendations

The ABFA enhancements described in this report, such as calculations

with moving/transient sources, a meteorological data interface, and map

displays generated from digitized feature data, significantly improve the

program’s utility in both operational and research settings. To a great

extent, the original goal of the ABFA program, to make the current

generation of advanced sound propagation models conveniently available

for realistic battlefield acoustic and noise impact predictions, has been now

realized. Nonetheless, there are still many worthwhile improvements that

could be made. Four such improvements recommended here for future

consideration are as follows:

1. Extension of the library of source (target) signatures. Currently, the

signature library is rather small (with about 25 signatures) and

consists primarily of tracked ground vehicles. The signatures also

have a low resolution in the frequency domain. It would be desirable

to extend the library, in particular with regard to aircraft. Interfacing

the program with source models, such as the recently developed

DOD acoustic helicopter model, should be considered.

2. Development of an expert system for setting the propagation table

parameters. Users experienced in outdoor sound propagation

generally recognize how to set the propagation table parameters

appropriately. However, this task is much more challenging for

non-experts.

3. Calculations of seismic sensor performance. Many U.S. Army

platforms having acoustic sensors also have seismic ones. Much of the

functionality and organization of the ABFA program would be well

suited to seismics. Additional propagation models would need to be

introduced into the program, along with graphical user-interface

structures to set up the positions of the seismic sensors and the

ground elastic properties.

4. Assimilation of meteorological data from multiple sources. Currently,

ABFA accesses weather data from only one data source at a time.

The data source could be either surface weather observations or a set

of vertical profiles. It would be desirable to have capabilities for

merging weather data from a variety of sources. For example,

33
low-resolution global forecast data could be merged with local

surface data or soundings. Development of tools for accomplishing

tasks such as this is currently an active area of atmospheric research,

and ABFA might be able to take advantage of the recent progress.

34
Acknowledgments

Most of the improvements described in this report were carried out with

funding from the National Ground Intelligence Center, administered by

Robert Grachus. Funding from a U.S. Army Research Laboratory (ARL)

Director’s Research Initiative, “Modeling Battlefield Acoustic Detection by

Advanced ATR Algorithms and the Human Auditory System,” supported

development of the interface between the Acoustic Battlefield Aid (ABFA)

and the Automatic Target Recognition (ATR) Acoustic Database.

The Java-based capability for retrieving weather data over the Internet

was developed primarily by Bruce VanAartsen of TASC/Litton, under

contract from ARL. The original capability for initializing ABFA from the

ATR Acoustic Database was developed by Greg Szeto, a student in the

Science Engineering and Apprenticeship Program (SEAP) administered by

George Washington University. Most of the graphical user-interface for

ground parameters was developed by Meredith Hutchinson, also a SEAP

student. We furthermore thank Steve Tenney and Alan Wetmore for their

helpful discussions on geographical information sources and other topics.

In Memoriam. One of the authors of this report, Anh Nguyen, passed

away while this work was in progress. The U.S. Army acoustical

community lost one of its most dedicated and skilled software developers.

We greatly miss our quiet and kind colleague.

35
Bibliography

Crocker, M. J. (1997): Introduction. In Encyclopedia of Acoustics,

Crocker, M. J., editor, volume 1, Wiley-Interscience, New York, 3–19.

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37

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NSN 7540-01-280-5500 Standard Form 298 (Rev. 2-89)

Prescribed by ANSI Std. Z39-18

298-102

Sound Exposure Calculations for Transient Events and Other Improvements

to an Acoustical Tactical Decision Aid

August 2002 Final, 7/1/01–1/15/02

Recent enhancements to an acoustical tactical decision aid, called the Acoustic Battlefield Aid (ABFA), are

described. ABFA predicts the effects of the atmosphere and local terrain on the performance of acoustical

sensors, using advanced sound propagation models. Among the enhancements are (1) sound-exposure and

detection calculations for moving and transient sources, (2) new display capabilities including loading of

vector-map features from CDs, (3) an interactive menu for entering and managing acoustical and meteorological

ground properties, (4) initialization of runs from field trials stored in the U.S. Army Research Laboratory's

Automatic Target Recognition Database, (5) a Java-based interface to numerical weather forecast data over the

Internet, and (6) creation of a Windows executable version using the Matlab compiler.

Sound propagation, acoustic sensors, geographical information systems

Unclassified

ARL-TR-2757

2FEH26

622784H7111

AH71

62784A

ARL PR:

AMS code:

DA PR:

PE:

Approved for public release; distribution unlimited.

44

Unclassified Unclassified SAR

220 Seventh Street NE

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U.S. Army Research Laboratory

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39

D. Keith Wilson, V. Anh Nguyen, Nassy Srour, and John Noble 

2800 Powder Mill Road

Adelphi, MD 20783-1197