Performance Prediction for Coherent Noise Radars Using the Correlation Coefficient

TL;DR

This paper demonstrates that the correlation coefficient can effectively predict the performance of coherent noise radars across different ranges, providing an alternative to traditional SNR-based methods.

Contribution

It derives the range dependence of the correlation coefficient and integrates it with ROC analysis to predict radar performance, offering a new perspective beyond SNR.

Findings

Correlation coefficient varies with range and can predict radar detection performance.

Derived ROC curves for noise radars using the correlation coefficient.

Results align with conventional radar performance metrics.

Abstract

Noise radars can be understood in terms of a correlation coefficient which characterizes their detection performance. Although most results in the literature are stated in terms of the signal-to-noise ratio (SNR), we show that it is possible to carry out performance prediction in terms of the correlation coefficient. To this end, we derive the range dependence of the correlation coefficient. We then combine our result with a previously-derived expression for the receiver operating characteristic (ROC) curve of a coherent noise radar, showing that we can obtain ROC curves for varying ranges. A comparison with corresponding results for a conventional radar employing coherent integration shows that our results are sensible. The aim of our work is to show that the correlation coefficient is a viable adjunct to SNR in understanding radar performance.