# OTFS Radar Waveform Design Based on Information Theory

## TL;DR

This paper introduces a new radar waveform design using OTFS and information theory to improve target information extraction.

## Contribution

A novel OTFS waveform design approach based on maximizing conditional mutual information and minimizing autocorrelation and cross-correlation.

## Key findings

- Optimized OTFS waveforms outperform random waveforms in target information extraction.
- Minimizing ASaCC improves radar cognitive capability.
- CMI is a promising metric for waveform design in radar systems.

## Abstract

In this work, we consider the waveform design for radar systems based on orthogonal time–frequency space (OTFS). The conditional mutual information (CMI), chosen as a promising metric for assessing the radar cognitive capability, serves as the criterion for OTFS waveform design. After formulating the OTFS waveform design problem based on maximizing CMI, we propose an equivalent waveform processing approach by minimizing the autocorrelation sidelobes and cross-correlations (ASaCC) of the OTFS transmitting matrix. Simulation results demonstrate that superior performance in target information extraction is achieved by the optimized OTFS waveforms compared to random waveforms.