MATLAB Implementation Methods for Radar Moving Target Detection

This article presents MATLAB implementation methods for radar moving target detection. Radar moving target detection is a fundamental signal processing technique used to analyze radar signals for determining specific target parameters including distance, velocity, and azimuth angle. To achieve this objective, we implement two distinct approaches: Fast Fourier Transform (FFT) analysis and Finite Impulse Response (FIR) filtering.

First, we employ the FFT method to analyze frequency components within radar signals. The FFT algorithm, widely used in digital signal processing, efficiently converts signals from the time domain to the frequency domain. In our MATLAB implementation, we utilize the built-in fft() function to compute the frequency spectrum, enabling identification of characteristic frequency components that correspond to target motion states. The implementation typically involves proper signal windowing using functions like hamming() or hanning() to reduce spectral leakage before applying the FFT operation.

Second, we implement FIR filtering techniques for radar signal preprocessing. FIR filters represent a class of digital filters that remove unwanted frequency components from digital signals through convolution operations. In radar moving target detection applications, we design FIR filters using MATLAB's filter design toolbox (filterDesigner) or functions like fir1() to eliminate noise and clutter interference, thereby improving target detection accuracy. The filter implementation involves specifying appropriate cutoff frequencies and filter order based on the radar system requirements.

By combining both FFT spectral analysis and FIR filtering methodologies in our MATLAB implementation, we achieve comprehensive radar signal processing capabilities that enable accurate analysis and detection of moving target characteristics. The complete workflow includes signal acquisition, preprocessing with FIR filters, frequency domain transformation using FFT, and subsequent target parameter extraction algorithms.