A track-before-detect algorithm with thresholded observations

A track-before-detect algorithm with thresholded
observations and closely-spaced targets
Emanuele Grossi
Marco Lops
Luca Venturino
Dipartimento di Ingegneria Elettrica e dell’Informazione
Università degli Studi di Cassino e del Lazio Meridionale
{e.grossi, lops, l.venturino}@unicas.it
GTTI, Ancona, 2013
Multi-frame detection: two-stage approach
raw data from
the sensor
traditonal
detector
list of
candidate
detections
TBD
processor
to the tracker
γ2
γ1
buffer
(L − 1 frames)
The traditional detector operates on a scan-by-scan basis and
provides a list of candidate detections
The primary threshold γ1 is set lower than that used in traditional
single-scan detection, causing an increment of both PD and FAR
The TBD processor exploits data correlation over multiple
frames to confirm or delete each candidate detection
The goal is to restore FAR to an acceptable level while
maintaining part (if not all) of the detection gain
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TBD processor
1
L−1
2
L
space
(n − L + 1)T
time
(n − L + 2)T
nT
a trajectory
cones of physically
admissible trajectories
observation surviving
the first stage
observation censored
by the first stage
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TBD processor
Step 1
Step 2
Estimated trajectories
false trajectory
false trajectory
ctory
tra je
target
ory
ct
tra je
target
SDR ≷ γ2
SDR ≷ γ2
false plot linked to
the target trajectory
jectory
target tra
target trajectory
target tra jec
tory
time
SDR ≷ γ2
true plot
false plot
time
estimated trajectory
space
plot of the weak target
linked to the trajectory
of the strong target
space
space
target tra jec
tory
time
1) Compute the best trajectory for each plot as in [1]
2) Extract the dominant trajectories and remove their plots
3) Iterate steps 1-2 until all trajectories are extracted
4) Compare the SDR of estimated trajectories against γ2
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Experimental Setup
radar parameters
range
azimuth
range accuracy
azimuth accuracy
scan duration
FARin
FARout
40 to 140 km
−60◦ to 60◦
20 m
0.5◦
1s
1000 per min
1 per min
target parameters
number
initial range
initial azimuth
direction
velocity
4 triplets
random in [50, 130] km
random in [−50◦ , 50◦ ]
random
random in [0, 300] m/s
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PD and RMSE
1
1
d = 1 km
Targets 2 and 3
0.8
SDR = 15 dB
0.8
Target 1, SDR = 12 dB
PD
0.6
PD
0.6
0.4
0.4
0.2
0.2
0
0
900
900
850
SDR = 9 dB
850
all SDRs
800
750
750
RMSE [m]
RMSE [m]
All targets, all SDRs
800
700
650
Target 1, SDR = 12 dB
SDR = 9 dB
700
650
Targets 2 and 3
600
550
500
600
L=1
L = 10, algorithm in [1]
L = 10, proposed algorithm
5
10
15
20
SDR of Targets 2 and 3 [dB]
25
500
0
SDR = 15 dB
L=1
L = 10, algorithm in [1]
L = 10, proposed algorithm
550
1
2
3
4
d [km]
5
6
7
8
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