Multi-Bernoulli filtering for initially unresolved targets in clutter

Qin Lu; Karl Granström; Yaakov Bar-Shalom; Peter Willett

doi:10.1117/12.2229638

17 May 2016 Multi-Bernoulli filtering for initially unresolved targets in clutter

Qin Lu, Karl Granström, Yaakov Bar-Shalom, Peter Willett

Proceedings Volume 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV; 98421J (2016) https://doi.org/10.1117/12.2229638
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

Abstract

Multiple target tracking (MTT) is a challenging task that aims to estimate the number of targets and their states in the presence of process noise, measurement noise and data association uncertainty. This paper considers a special MTT problem characterized by additional complexity. In this problem, multiple targets are launched simultaneously in nearby locations at the same speed with slightly diﬀerent directions. As the distances be-tween the initial locations of these targets are smaller than the resolution of the sensor, this results in merged measurements, i.e., unresolved tracks at the very beginning. To deal with this problem, the recently proposed Multi-Bernoulli (MB) ﬁlter is applied. Using a model for the merged measurements, simulation results with 2-D Cartesian measurements in an optical sensor’s focal plane in the presence of clutter show that the initially unresolved tracks become resolved with MB ﬁltering a few time steps after the measurements become resolved. Thus, the MB ﬁlter is capable of keeping track of the number of targets and their corresponding states when they are initially unresolved.

Citation Download Citation

Qin Lu, Karl Granström, Yaakov Bar-Shalom, and Peter Willett "Multi-Bernoulli filtering for initially unresolved targets in clutter", Proc. SPIE 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV, 98421J (17 May 2016); https://doi.org/10.1117/12.2229638

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