Mitigation of Ground Clutter in Airborne Bistatic Radar Systems
Paper in proceedings, 2020

Space-Time Adaptive Processing is a commonly used technique to mitigate ground clutter reflections from an airborne radar system. It estimates a covariance matrix based on spatial and temporal information, and the estimate is thereafter used to suppress the ground clutter. In a side-looking monostatic radar system, the estimate is rather straight forward based on radar observations. However, in this paper, we consider bistatic systems where the power of adaptivity is limited due to nonstationarity of the ground clutter reflections over the range dimension. To overcome this, scenario dependent transformations are commonly used when forming the sample covariance matrix. In this contribution we instead investigate a detector where the clutter covariance matrix is determined from the geometry of the bistatic scenario. Using a Monte-Carlo simulation, we investigate how sensitive the detector is to errors in the assumed geometry, and compare this with state-of-the-art adaptive methods. The results indicates that a good clutter rejection is obtained for errors of order 103 m for assumed transmitter position and 100km/h for assumed transmitter velocity.

Space-Time Adaptive Processing

bistatic radar systems

ground clutter mitigation.

Author

Jacob Klintberg

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering, Signal Processing

Tomas McKelvey

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering, Signal Processing

Patrik Dammert

Saab AB

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering, Signal Processing

Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop

2151870X (eISSN)

9104314

202020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)
Hangzhou, China,

Passiv and multistatic radar

VINNOVA, 2017-11-10 -- 2021-12-31.

Subject Categories

Probability Theory and Statistics

Control Engineering

Signal Processing

DOI

10.1109/SAM48682.2020.9104314

More information

Latest update

1/7/2021 7