Joint Filter and Waveform Design for Radar STAP in Signal Dependent Interference
For radar systems engineers, this work provides a computationally feasible approach to joint waveform and filter design in STAP, though the algorithms remain computationally intensive.
The paper addresses joint receiver filter and waveform design for radar space-time adaptive processing (STAP) in signal-dependent interference. It proposes alternating minimization algorithms that iteratively optimize the filter and waveform, achieving convergence to a stationary point.
Waveform design is a pivotal component of the fully adaptive radar construct. In this paper we consider waveform design for radar space time adaptive processing (STAP), accounting for the waveform dependence of the clutter correlation matrix. Due to this dependence, in general, the joint problem of receiver filter optimization and radar waveform design becomes an intractable, non-convex optimization problem, Nevertheless, it is however shown to be individually convex either in the filter or in the waveform variables. We derive constrained versions of: a) the alternating minimization algorithm, b) proximal alternating minimization, and c) the constant modulus alternating minimization, which, at each step, iteratively optimizes either the STAP filter or the waveform independently. A fast and slow time model permits waveform design in radar STAP but the primary bottleneck is the computational complexity of the algorithms.