Self-Harmonic Suppression Algorithms for Effective Detection in Nonlienar FMCW Radar

Nonlinear radars detect electronic targets by capturing weak nonlinear responses from electronic devices and excluding linear objects. However, inducing and capturing these responses require high-power and high-gain amplifiers, which inevitably produce self-generated harmonics. To suppress these harmonics, this study developed a technique that predicts their generation paths and collects look-up table (LUT) data based on the distances to linear objects. The optimal weights for the LUT data were derived using the particle swarm optimization (PSO) algorithm. Measurements were performed with three nonlinear targets at 6 m and walls at 2.5 m and 4 m. The results indicate improved detection performance, with a reduced cell-average constant false alarm rate (CA-CFAR) threshold at the target position when the proposed algorithm was applied.