# Smart Interference Signal Design to a Cognitive Radar

2023 IEEE RADAR CONFERENCE, RADARCONF23（2023）

Abstract

This paper addresses an adversarial inference problem involving cognitive radars. The game theoretic framework described in this paper comprises "us" and an "adversary". Our goal is to design an external interference signal that confuses the adversary radar with given information of the signals of the radar. The optimization problem is formulated such that the signal power of the designed interference is minimized while enforcing the probability that the signal-to-clutter-plusnoise ratio (SCNR) of the radar exceeds a certain SCNR level to be less than a specified threshold. The resulting problem is a challenging optimization problem since the constraint is based on a probability density function (PDF), which is non-differentiable. By taking an expected value of the SCNR, the problem is relaxed to a convex problem using the semidefinite relaxation. The simulation results verify the performance of the designed interference using the high-fidelity modeling and simulation tool, RFView.

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Key words

cognitive fully adaptive radar,Green's function,non-convex quadratic constrained quadratic programming,semidefinite relaxation,semidefinite programming

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