Application of the Kalman-Levy filter for tracking maneuvering targets

Abhijit Sinha; Thiagalingam Kirubarajan; Yaakov Bar-Shalom

doi:10.1117/12.542896

25 August 2004 Application of the Kalman-Levy filter for tracking maneuvering targets

Abhijit Sinha, Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 5428, Signal and Data Processing of Small Targets 2004; (2004) https://doi.org/10.1117/12.542896
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

In target tracking algorithms using Kalman filtering-like approaches, the standard assumptions are Gaussian process and measurement noise models. Based on these assumptions, the Kalman filter is widely used in single or multiple filter versions (e.g., in an Interacting Multiple Model-IMM-estimator). The over-simplification resulting from the above assumptions can cause severe degradation in tracking performance. Of particular concern is the simplistic white noise or Wiener process acceleration models used to handle maneuvering targets. Presence of heavy-tailed noise in the observation process is another concern. In this paper we explore the application of Kalman-Levy filter to handle maneuvering targets. This filter assumes a heavy tailed noise distribution known as the Levy distribution. Unlike in the case of Gaussian distribution, the existence of the covariance is not guaranteed in this case. Due to the heavy tailed nature of the assumed distribution, the Kalman-Levy filter is more effective in the presence of large errors that can occur, for example, due to the onset of acceleration or deceleration. However, for the same reason, the performance of Kalman-Levy filter in non-maneuvering portion of track is worse than a Kalman filter's. This motivates us to develop an IMM estimator incorporating a Kalman filter and a Kalman-Levy filter. The performance of this filter is compared with an IMM estimator with two standard Kalman filters in a scenario from the 4th Navy tracking benchmark problem. It is found that the IMM estimator with a Kalman-Levy filter performs better than the other IMM estimator in both maneuvering and non-maneuvering portion of target flight.

Citation Download Citation

Abhijit Sinha, Thiagalingam Kirubarajan, and Yaakov Bar-Shalom "Application of the Kalman-Levy filter for tracking maneuvering targets", Proc. SPIE 5428, Signal and Data Processing of Small Targets 2004, (25 August 2004); https://doi.org/10.1117/12.542896

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