Target selection in a multitrack environment

Kaipei Yang; Meir Danino; Yaakov Bar-Shalom

doi:10.1117/12.2563995

22 April 2020 Target selection in a multitrack environment

Kaipei Yang, Meir Danino, Yaakov Bar-Shalom

Proceedings Volume 11423, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIX; 1142307 (2020) https://doi.org/10.1117/12.2563995
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

The problem of selecting a target of interest for interdiction in the presence of several spurious tracks that are meant to confuse the defense has been around for several decades. The spurious tracks are from the objects released from the target of interest and they move forward at the same speed as the target of interest. They separate due to a release velocity orthogonal to the forward motion. The main means of carrying out the discrimination between the target of interest and the spurious tracks discussed in the literature is using some features, which, however, are not always available. The present work considers this problem when the extraneous tracks “look” the same as the target of interest for the sensor tracking them, i.e., they have no distinguishing features. It is shown that the history of the track kinematics — the evolution of the tracks — can be used via “track segment association” to select the track of the target of interest from the several tracks in the field of view of the sensor. One of the challenges of this work is that, with limited resolution capability, the observations from the sensor are unresolved when the extraneous targets start separating. In this work, the data association and tracking are handled separately from track segment association, which reduces the complexity of the problem and is shown to have timely and reliable results in the simulations.

Conference Presentation

Citation Download Citation

Kaipei Yang, Meir Danino, and Yaakov Bar-Shalom "Target selection in a multitrack environment", Proc. SPIE 11423, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIX, 1142307 (22 April 2020); https://doi.org/10.1117/12.2563995

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