Validation volume reduction with tracking in sensor coordinates

Shida Ye; Yaakov Bar-Shalom; Peter Shea; Chee-Yee Chong

doi:10.1117/12.2664125

14 June 2023 Validation volume reduction with tracking in sensor coordinates

Shida Ye, Yaakov Bar-Shalom, Peter Shea, Chee-Yee Chong

Proceedings Volume 12547, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII; 1254705 (2023) https://doi.org/10.1117/12.2664125
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

Tracking in sensor coordinates has numerous benefits, because the filter bypasses the burden of nonlinear coordinates transformation, if consistency in the Cartesian space is guaranteed. Taking advantage of recent breakthroughs in coordinate conversion methods related to bistatic r-u-v (range and direction sines u,v ), we develop the r-u-v filter to optimize the association gate volume while maintaining Cartesian consistency. The paper focuses on materializing theoretical gains due to r-u-v tracking in a scenario with a glide vehicle subject to aerodynamic drag and gravity in a guided trajectory. Previous r-u-v filters are mixed-coordinate filters because realistic dynamics is difficult to express in r-u-v, but the present work manages to account for drag, gravity and guidance in r-u-v state equations without excessive complexity. Linear measurement model helps reduce gate volume, especially by accentuating the range accuracy of the sensor. In the presence of the “contact lens” phenomenon, gate volume reduction can be furthered by replacing the Gaussian ellipsoid gate which has a lot of empty space with a fuller and better fitted contact-lens-shaped gate region. Comparative simulations show that benefits are dependent on the sampling frequency and can be attributed to the choice of coordinates used by the filter.

Conference Presentation

Citation Download Citation

Shida Ye, Yaakov Bar-Shalom, Peter Shea, and Chee-Yee Chong "Validation volume reduction with tracking in sensor coordinates", Proc. SPIE 12547, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII, 1254705 (14 June 2023); https://doi.org/10.1117/12.2664125

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