Short‐range ground moving target indication in forward looking airborne radar based on elevation prefiltering

Abstract

Clutter suppression for short-range ground moving target indication in forward looking airborne radar is a challenging problem because of the range-dependent clutter. If the pulse repetition frequency is chosen so high that radar clutter is range ambiguous, then additional blind velocities at short-range induced by far-range clutter will occur. To eliminate these additional blind velocities, an efficient beamspace-based adaptive prefiltering method in elevation is proposed in this study to suppress ambiguous far-range clutter. The proposed beamformer can provide nearly optimal adapted elevation pattern because of the improved training data selection strategy. After eliminating the impact of ambiguous far-range clutter, the Dopplercompensation-based space-time adaptive processing method could be carried out to suppress residual range-dependent shortrange clutter. In addition, the proposed prefiltering method is computationally efficient, and hence it is suitable for engineering application.

Airborne forward‐looking radar imaging approach via modified propagator method in planar phased array

“…Forward-looking radar imaging can image the forward-looking area with a high resolution, which can be widely applied to military and civilian fields such as precision guidance, remote sensing mapping, automatic driving etc [1][2][3][4][5][6][7][8][9]. For traditional synthetic aperture radar (SAR) imaging techniques, there exists a significant coupling between azimuth and range dimensions in forward-looking scenarios.…”

“…In recent years, researchers have carried out a lot of research on forward-looking radar imaging algorithms. The main algorithms include monopulse radar forward-looking imaging (FLMC) [5][6][7][8], scanning radar deconvolution FLMC [9][10][11][12][13], bistatic forward-looking SAR (BFSAR) imaging [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29], sector imaging radar for enhanced vision (SIREV) [30][31][32][33][34] and multi-channel FLMC algorithms [35][36][37][38][39][40][41][42][43].…”