# Adaptive Detection of Coherent Radar Targets in the Presence of Noise Jamming

## TL;DR

This paper presents adaptive detection schemes for radar targets in the presence of noise-like jammers that use noise cover pulses to mask targets, employing modified likelihood ratio tests and cyclic optimization.

## Contribution

It introduces novel adaptive decision schemes with cyclic optimization for detecting targets amidst sophisticated noise-like jammers in radar systems.

## Key findings

- Effective detection performance demonstrated through simulations
- Robustness against active and switched-off jammers
- Improved detection accuracy over traditional methods

## Abstract

In this paper, we devise adaptive decision schemes to detect targets competing against clutter and smart noise-like jammers (NLJ) which illuminate the radar system from the sidelobes. Specifically, the considered class of NLJs generates a pulse of noise (noise cover pulse) that is triggered by and concurrent with the received uncompressed pulse in order to mask the skin echo and, hence, to hide the true target range. The detection problem is formulated as a binary hypothesis test and two different models for the NLJ are considered. Then, ad hoc modifications of the generalized likelihood ratio test are exploited where the unknown parameters are estimated by means of cyclic optimization procedures. The performance analysis is carried out using simulated data and proves the effectiveness of the proposed approach for both situations where the NLJ is either active or switched off.