Multichannel signal detection in interference and noise when signal mismatch happens

TL;DR

This paper introduces two selective detectors and a tunable detector for multichannel signal detection in interference and noise with signal mismatch, providing analytical performance expressions and demonstrating their effectiveness through simulations.

Contribution

It proposes a tunable detector that adjusts robustness to signal mismatch, enhancing detection flexibility and performance in multichannel scenarios.

Findings

The proposed detectors have analytical PD and PFA expressions.

The tunable detector can balance detection and robustness.

Simulations confirm the detectors' effectiveness.

Abstract

In this paper, we consider the problem of detecting a multichannel signal in interference and noise when signal mismatch happens. We first propose two selective detectors, since their strong selectivity is preferred in some situations. However, these two detectors would not be suitable candidates if a robust detector is needed. To overcome this shortcoming, we then devise a tunable detector, which is parametrized by a non-negative scaling factor, referred to as the tunable parameter. By adjusting the tunable parameter, the proposed detector can smoothly change its capability in rejecting or robustly detecting a mismatch signal. Moreover, one selective detector and the tunable detector with an appropriate tunable parameter can provide nearly the same detection performance as existing detectors in the absence of signal mismatch. We obtain analytical expressions for the probabilities of detection (PDs) and probabilities of false alarm (PFAs) of the three proposed detectors, which are verified by Monte Carlo simulations.