Dimension-reduced bi-iterative space–time adaptive processing method for airborne radar

Abstract

A novel bi-iterative dimension-reduced space–time adaptive processing (STAP) algorithm for clutter suppression and moving target detection in airborne radar system is proposed. A dimension-reduced processing in both space and time is firstly performed. Then a bi-quadratic cost function is constructed to estimate the dimension-reduced spatiotemporal filter coefficients, which are used for suppressing the clutter and keeping the target signal. An optimal solution to the cost function can be obtained efficiently by a bi-iteration algorithm. Theoretical analysis and computer simulation results illustrate that the algorithm has fast convergence, low computation load and sampling requirements. The results of experiment by using the measured data show the validity of the proposed algorithm.

Keywords

• airborne radar
• radar signal processing
• object detection
• radar clutter
• space-time adaptive processing
• iterative methods
• airborne radar system
• dimension-reduced processing
• bi-quadratic cost function
• dimension-reduced spatiotemporal filter coefficients
• bi-iteration algorithm
• dimension-reduced bi-iterative space–time adaptive processing method
• novel bi-iterative dimension-reduced space–time adaptive processing algorithm
• clutter suppression
• moving target detection