Abstract
This paper proposes a novel joint probabilistic data association (JPDA) filter for joint target tracking and track maintenance under unknown detection probability and clutter rate. The proposed algorithm consists of two main parts: (1) the standard JPDA filter with a Poisson point process birth model for multi-object state estimation; and (2) a multi-Bernoulli filter for detection probability and clutter rate estimation. The performance of the proposed JPDA filter is evaluated through empirical tests. The results of the empirical tests show that the proposed JPDA filter has comparable performance with ideal JPDA that is assumed to have perfect knowledge of detection probability and clutter rate. Therefore, the algorithm developed is practical and could be implemented in a wide range of applications.
Highlights
There has been increasing attention on utilisation of small autonomous systems in military and civil applications
Motivated by the above observations, this paper aims to propose an enhanced version of joint probabilistic data association (JPDA) that can accommodate the unknown detection probability and clutter rate
This paper developed an enhanced version of JPDA by incorporating with the multi-Bernoulli filter to accommodate the unknown detection probability and clutter rate
Summary
There has been increasing attention on utilisation of small autonomous systems in military and civil applications. The issue is that the operations of these small autonomous systems are constrained by limited payload, as well as limited operation time and endurance. This has led to proliferation of lightweight, low-cost and energy efficient on-board sensors. Reliable and autonomous target tracking is a fundamental aspect of situation awareness for autonomous systems [1,2,3]. Applying low-cost and lightweight on-board sensors in target tracking imposes additional challenges to the tracking problem since they are likely to contain some degree of uncertainties. Low-cost sensors are generally subject to a high clutter rate and low detection probability
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