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Space-time adaptive processing (STAP) is an effective method for multi-input multi-output (MIMO) radar systems to identify moving targets in the presence of multiple interferers. The idea of joint optimization in both spatial and temporal domains for radar detection is consistent with the symbol-level precoding (SLP) technique for MIMO communication systems, that optimizes the transmit waveform according to instantaneous transmitted symbols. Therefore, in this paper we combine STAP and constructive interference (CI)-based SLP techniques to realize dual-functional radar-communication (DFRC). The radar output signal-to-interference-plus-noise ratio (SINR) is maximized by jointly optimizing the transmit waveform and receive filter, while satisfying the communication quality-of-service (QoS) constraints and the constant modulus power constraint. An efficient algorithm based on majorization-minimization (MM) and nonlinear equality constrained alternative direction method of multipliers (neADMM) methods is proposed to solve the non-convex optimization problem. Simulation results verify the effectiveness of the proposed DFRC scheme and the associate algorithm.
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This content will become publicly available on June 9, 2025
Exploitation of Symmetrical Non-Convexity for Symbol-Level DFRC Signal Design
Constructive interference exploited by symbol-level (SL) signal processing is a promising solution for addressing the inherent interference problem in dual-functional radar-communication (DFRC) signal designs. This paper considers an SL-DFRC signal design problem which maximizes the radar performance under communication performance constraints. We exploit the symmetrical non-convexity property of the communication-independent radar sensing metric to develop low- complexity yet efficient algorithms. We first propose a radar-to- DFRC (R2DFRC) algorithm that relies on the non-convexity of the radar sensing metric to find a set of radar-only solutions. Based on these solutions, we further exploit the symmetrical property of the radar sensing metric to efficiently design the DFRC signal. Since the radar sensing metric is independent of the communication channel and data symbols, the set of radar-only solutions can be constructed offline, therefore reducing the computational complexity. We then develop an accelerated R2DFRC algorithm that further reduces the complexity. Finally, we demonstrate the superiority of the proposed algorithms compared to existing methods in terms of both radar sensing and communication performance as well as computational complexity.
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- Award ID(s):
- 2008724
- PAR ID:
- 10564888
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 978-1-7281-9054-9
- Page Range / eLocation ID:
- 299 to 304
- Format(s):
- Medium: X
- Location:
- Denver, CO, USA
- Sponsoring Org:
- National Science Foundation
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