Frequency Permutation Subsets for Joint Radar and Communication

TL;DR

This paper introduces a novel subset selection and encoding approach for frequency permutation waveforms in joint radar and communication systems, enhancing error rates and target detection accuracy.

Contribution

It proposes new subset selection methods, an efficient encoding scheme, and analysis techniques to improve both communication reliability and radar sensing performance.

Findings

Improved block error rate with subset selection methods

Enhanced radar target detection accuracy through ambiguity function analysis

Reduced sidelobe levels using Costas array properties

Abstract

This paper focuses on waveform design for joint radar and communication systems and presents a new subset selection process to improve the communication error rate performance and global accuracy of radar sensing of the random stepped frequency permutation waveform. An optimal communication receiver based on integer programming is proposed to handle any subset of permutations followed by a more efficient sub-optimal receiver based on the Hungarian algorithm. Considering optimum maximum likelihood detection, the block error rate is analyzed under both additive white Gaussian noise and correlated Rician fading. We propose two methods to select a permutation subset with an improved block error rate and an efficient encoding scheme to map the information symbols to selected permutations under these subsets. From the radar perspective, the ambiguity function is analyzed with regards to the local and the global accuracy of target detection. Furthermore, a subset selection method to reduce the maximum sidelobe height is proposed by extending the properties of Costas arrays. Finally, the process of remapping the frequency tones to the symbol set used to generate permutations is introduced as a method to improve both the communication and radar performances of the selected permutation subset.