Abstract
In many wireless sensors, the target kinematic states include location and Doppler information that can be observed from a time series of range and velocity measurements. In this work, we present a tracking strategy for comprising target velocity components as part of the measurement supplement procedure and evaluate the advantages of the proposed scheme. Data association capability can be considered as the key performance for multi-target tracking in an active sonar system. Then, we proposed an enhanced Doppler data association (DDA) scheme which exploits target range and target velocity components for linear multi-target tracking. If the target velocity measurements are not incorporated into target kinematic state tracking, the linear filter bank for the combination of target velocity components can be implemented. Finally, a significant enhancement in the multi-target tracking capability provided by the proposed DDA scheme with the linear multi-target combined probabilistic data association method is demonstrated in a sonar underwater scenario.
Highlights
Besides position measurements, Doppler measurement can offer supplementary statistics about target state, which would enhance tracking performance [1]
The trace of the k-th target can be expressed as xkp+1 = Fp xkp + vkp where xkp is the k-th target kinematic state at time p, Fp denotes the transition matrix of target state and vkp describes the vector of additive white Gaussian noise (AWGN) with zero mean and covariance
Doppler measurements versus range for continuous wave (CW) mode
Summary
Doppler measurement can offer supplementary statistics about target state, which would enhance tracking performance [1]. A consensus dual-stage nonlinear filter algorithm was presented to solve the Doppler-only target tracking problem in a distributed and scalable way [17] Based on such a decomposition, a novel dual-stage filter for centralized multi-sensor. In order to improve the performance of multiple extended target tracking, we analyze the advantage of combining target velocity measurements into the target state vectors, present an advanced Doppler data association (DDA) scheme which employs target range and velocity components for improving target tracking performance. The proposed scheme offers a robust usage of velocity observations that would realize significant performance enhancements to those stated in the literature without the supplementary computational burden due to the use of nonlinear filters [28].
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