Joint Design of Autocorrelation and Spectral Characteristics of Radar Waveforms

• Published in: IEEE access 2024, Vol.12, p.98075-98082
• Main Authors: Aldayel, Omar, Almohimmah, Esam M., Ragheb, Amr M., Almaiman, Ahmed, Alshebeili, Saleh A.
• Format: Article
• Language: English
• Subjects: Autocorrelation; autocorrelation sidelobes; Convergence; dual-objective optimization; frequency nulling; Interference; Minimization; Radar; spectral shaping; stopbands; Transforms; Vectors; Waveform design
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2024.3427860

One important aspect of radar systems is the transmit waveform, which plays a key role in defining system's detection capability and target resolution. Waveforms with good autocorrelations and increased bandwidth are preferred for this purpose. However, waveforms with large bandwidths may cause spectral interference with neighboring channels. As a result, it is crucial to establish frequency stopbands within the spectrum of transmit waveform to mitigate potential interference. While it's easy to independently design waveforms with either good autocorrelation or specific frequency stopbands, designing radar waveforms that excel in both aspects simultaneously is a difficult task. In this paper, we address this challenge by optimizing radar waveform with dual objectives: minimizing autocorrelation sidelobes to enhance system performance and managing spectral characteristics to expand bandwidth while avoiding interference with other frequency bands. We first transform the dual-objective function into a single-objective function encompassing both correlation and stopband properties. We propose a novel algorithm to solve this problem and rigorously demonstrate its convergence through mathematical proof, providing a robust foundation for practical implementation. We evaluate the algorithm's performance in challenging scenarios and demonstrate its effectiveness compared to recent approaches in the literature.