Waveform Optimization with SINR Criteria for FDA Radar in the Presence of Signal-Dependent Mainlobe Interference
Wenkai Jia, Andreas Jakobsson, and Wen-Qin Wang

TL;DR
This paper presents a novel waveform optimization and receiver design for FDA radar to enhance SINR amid mainlobe interference, using advanced filtering and optimization algorithms.
Contribution
It introduces a new FDA receiver framework and waveform optimization algorithms that effectively suppress mainlobe interference and improve SINR performance.
Findings
Enhanced interference suppression with the proposed methods.
Higher SINR achieved compared to non-optimized FDA systems.
Effective waveform and receiver design demonstrated through simulations.
Abstract
In this paper, we focus on the design of the transmit waveforms of a frequency diverse array (FDA) in order to improve the output signal-to-interference-plus-noise ratio (SINR) in the presence of signal-dependent mainlobe interference. Since the classical multi-carrier matched filtering-based FDA receiver cannot effectively utilize the waveform diversity of FDA, a novel FDA receiver framework based on multi-channel mixing and low-pass filtering is developed to keep the separation of the transmit waveform at the receiver side, while preserving the FDA range-controllable degrees of freedom. Furthermore, a range-angle minimum variance distortionless response beamforming technique is introduced to synthesize receiver filter weights with the ability to suppress a possible signal-dependent mainlobe interference. The resulting FDA transmit waveform design problem is initially formulated as an…
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