CoSTAP: Clutter Suppression in Co-Pulsing FDA-STAP

Range-dependent clutter suppression poses significant challenges in airborne frequency diverse array (FDA) radar, where resolving range ambiguity is particularly difficult. Traditional space-time adaptive processing (STAP) techniques used for clutter mitigation in FDA radars operate in the physical domain defined by first-order statistics. In this paper, unlike conventional airborne uniform FDA, we introduce a space-time-range adaptive processing (STRAP) method to exploit second-order statistics for clutter suppression in the newly proposed co-pulsing FDA radar. This approach utilizes co-prime frequency offsets (FOs) across the elements of a co-prime array, with each element transmitting at a non-uniform co-prime pulse repetition interval (C-Cube). By incorporating second-order statistics from the co-array domain, the co-pulsing STRAP or CoSTAP benefits from increased degrees of freedom (DoFs) and low computational cost while maintaining strong clutter suppression capabilities. However, this approach also introduces significant computational burdens in the coarray domain. To address this, we propose an approximate method for three-dimensional (3-D) clutter subspace estimation using discrete prolate spheroidal sequences (DPSS) to balance clutter suppression performance and computational cost. We first develop a 3-D clutter rank evaluation criterion to exploit the geometry of 3-D clutter in a general scenario. Following this, we present a clutter subspace rejection method to mitigate the effects of interference such as jammer. Compared to existing FDA-STAP algorithms, our proposed CoSTAP method offers superior clutter suppression performance, lower computational complexity, and enhanced robustness to interference. Numerical experiments validate the effectiveness and advantages of our method.

Co-Pulsing FDA Radar

Target localization based on frequency diverse array (FDA) radar has lately garnered significant research interest. A linear frequency offset (FO) across FDA antennas yields a range-angle dependent beampattern that allows for joint estimation of range and direction-of-arrival (DoA). Prior works on FDA largely focus on the one-dimensional linear array to estimate only azimuth angle and range while ignoring the elevation and Doppler velocity. However, in many applications, the latter two parameters are also essential for target localization. Further, there is also an interest in radar systems that employ fewer measurements in temporal, Doppler, or spatial signal domains. We address these multiple challenges by proposing a co-prime L-Shaped FDA, wherein co-prime FOs are applied across the elements of L-shaped co-prime array and each element transmits at a non-uniform co-prime pulse repetition interval (C$^3$ or C-Cube). This co-pulsing FDA yields significantly large degrees-of-freedom (DoFs) for target localization in the range-azimuth-elevation-Doppler domain while also reducing the time-on-target and transmit spectral usage. By exploiting these DoFs, we develop C-Cube auto-pairing (CCing) algorithm, in which all the parameters are ipso facto paired during a joint estimation. We show that C-Cube FDA requires at least $2\sqrt{Q+1}-1$ antenna elements and $2\sqrt{Q+1}-1$ pulses to guarantee perfect recovery of $Q$ targets as against $Q+1$ elements and $Q+1$ pulses required by both L-shaped uniform linear array and L-shaped linear FO FDA with uniform pulsing. Numerical experiments with our CCing algorithm show great performance improvements in parameter recovery, wherein C-Cube radar achieves at least $15\%$ higher target hit-rate with shorter dwell time than its uniform counterparts.