The trajectory of a supersonic bullet, which is subjected to drag and gravity, is curvilinear and the supersonic flight of the bullet generates a ballistic shock wave (SW). A model for the differential time of arrival (DTOA) of the SW at a pair of acoustic sensors is derived for a given bullet trajectory, which is fully described by seven parameters including the drag coefficient exponent and ballistic constant of the bullet. Assuming that the drag coefficient exponent is 0.5, the DTOA model is used to develop a nonlinear least-squares (NLS) method to estimate the other six trajectory parameters using DTOA of SW measurements from each node (which comprises a small acoustic sensor array) of an asynchronous sensor network. The position of the shooter and the muzzle speed of the bullet are then determined by tracing the estimated bullet trajectory back to topographic or man-made obstructions on a digital map. The effectiveness of the NLS method is verified using simulated data for different types of real bullets, and the error standard deviations in the parameter estimates are close to the Cramer-Rao lower bounds.

1.
R. C.
Maher
, “
Acoustical characterization of gunshots
,” in
Proceedings of the IEEE Workshop on Signal Processing Applications for Public Security and Forensics SAFE'07
(
2007
), pp.
109
113
.
2.
A.
Donzier
and
S.
Cadavid
, “
Small arm fire acoustic detection and localization systems: Gunfire detection system
,”
Proc. SPIE
5778
,
245
253
(
2005
).
3.
K. W.
Lo
and
B. G.
Ferguson
, “
Localization of small arms fire using acoustic measurements of muzzle blast and/or ballistic shock wave arrivals
,”
J. Acoust. Soc. Am.
132
,
2997
3017
(
2012
).
4.
G. L.
Duckworth
,
D. C.
Gilbert
, and
J. E.
Barger
, “
Acoustic counter-sniper system
,”
Proc. SPIE
2938
,
262
275
(
1997
).
5.
K. W.
Lo
, “
Supersonic bullet trajectory estimation using ballistic shock wave arrivals at an acoustic sensor array
,” in
Proceedings of ACOUSTICS
(
2016
), available at http://www.acoustics.asn.au/conference_proceedings/AASNZ2016/papers/p9.pdf (Last viewed February 21, 2017).
6.
J.
Bédard
and
S.
Paré
, “
Ferret, a small arms' fire detection system: Localization concepts
,”
Proc. SPIE
5071
,
497
509
(
2003
).
7.
K. W.
Lo
and
B. G.
Ferguson
, “
A ballistic model-based method for ranging direct fire weapons using the acoustic muzzle blast and shock wave
,” in
Proc. Intelligent Sensors Sensor Networks Inf. Process. ISSNIP
(
2008
), pp.
453
458
.
8.
K. W.
Lo
and
B. G.
Ferguson
, “
Acoustic ranging of small arms fire using a single sensor node collocated with the target
,”
J. Acoust. Soc. Am.
137
,
EL422
EL428
(
2015
).
9.
D.
Lindgren
,
O.
Wilsson
,
F.
Gustafsson
, and
H.
Habberstad
, “
Shooter localization in wireless microphone networks
,”
EURASIP J. Adv. Signal Process.
2010
,
690732
(
2010
), available at http://asp.eurasipjournals.springeropen.com/articles/10.1155/2010/690732 (Last viewed February 21, 2017).
10.
T.
Damarla
,
L. M.
Kaplan
, and
G. T.
Whipps
, “
Sniper localization using acoustic asynchronous sensors
,”
IEEE Sensors J.
10
,
1469
1478
(
2010
).
11.
P.
Volgyesi
,
G.
Balogh
,
A.
Nadas
,
C. B.
Nash
, and
A.
Ledeczi
, “
Shooter localization and weapon classification with soldier wearable networked sensors
,”
Technical Report TR No. ISIS-07-802
, Institute for Software Integrated Systems, Vanderbilt University (
2007
), available at http://www.isis.vanderbilt.edu/sites/default/files/Volgyesi_P_1_15_2007_Shooter_Lo.pdf (Last viewed February 21, 2017).
12.
K. W.
Lo
and
B. G.
Ferguson
, “
Simultaneous classification and ranging of direct fire weapons using an asynchronous acoustic sensor network
,” in
Proc. Intelligent Sensors Sensor Networks Inf. Process. ISSNIP
(
2011
), pp.
425
430
.
13.
S.
Hengy
,
P.
Duffner
,
S.
DeMezzo
,
S.
Heck
,
L.
Gross
, and
P.
Naz
, “
Acoustic shooter localisation using a network of asynchronous acoustic nodes
,”
IET Radar, Sonar Navig.
10
,
1528
1535
(
2016
).
14.
K. W.
Lo
and
B. G.
Ferguson
, “
Comparison of supersonic bullet ballistic models for accurate localization of small arms fire
,”
IET Radar, Sonar Navig.
10
,
1536
1540
(
2016
).
15.
R. J.
Kozick
,
G. T.
Whipps
, and
J. N.
Ash
, “
Supersonic projectile models for asynchronous shooter localization
,”
Proc. SPIE
8046
,
804604
(
2011
).
16.
T.
Mäkinen
and
P.
Pertilä
, “
Shooter localization and bullet trajectory, calibre, and speed estimation based on detected firing sounds
,”
Appl. Acoust.
71
,
902
913
(
2010
).
17.
M.
Cannella
,
P.
Cappa
, and
S. A.
Sciuto
, “
A novel approach for determining the trajectory and speed of a supersonic object
,”
Meas. Sci. Technol.
14
,
654
662
(
2003
).
18.
D.
Grasing
and
B.
Ellwood
, “
Development of acoustic sniper localization methods and models
,”
Proc. SPIE
7693
,
769312
(
2010
).
19.
P.
Weinacht
,
G. R.
Cooper
, and
J. F.
Newill
, “
Analytical prediction of trajectories for high velocity direct-fire munitions
,” ARL-TR-3567, U.S. Army Research Laboratory (
2005
), available at http://www.arl.army.mil/arlreports/2005/ARL-TR-3567.pdf (Last viewed February 21, 2017).
20.
E.
Danicki
, “
The shock wave-based acoustic sniper localization
,”
Nonlinear Anal.
65
,
956
962
(
2006
).
21.
B. M.
Sadler
,
T.
Pham
, and
L. C.
Sadler
, “
Optimal and wavelet-based shock wave detection and estimation
,”
J. Acoust. Soc. Am.
104
,
955
963
(
1998
).
22.
MathWorks Documentation on atan2
, available http://au.mathworks.com/help/matlab/ref/atan2.html (Last viewed January 23, 2017).
You do not currently have access to this content.