Implementation of MTD Processing Using FFT and FIR Methods

We implement MTD (Moving Target Detection) processing using both FFT (Fast Fourier Transform) and FIR (Finite Impulse Response) methods and conduct a comparative analysis.

In this experiment, we first process the data using the FFT method, which involves implementing a Fourier transform algorithm to convert time-domain signals into frequency-domain representations. The FFT approach typically utilizes efficient algorithms like Cooley-Tukey for rapid spectral analysis, enabling frequency component extraction through functions such as fft() in programming environments.

Subsequently, we process the same dataset using the FIR method, which employs digital filter design techniques with finite impulse response characteristics. This implementation involves creating filter coefficients using windowing methods (e.g., Hamming, Hanning) and applying convolution operations through filter design functions like fir1() for target signal enhancement.

By comparing the results from both methods, we evaluate their performance metrics in MTD processing, including computational efficiency, detection accuracy, and real-time processing capabilities. This comparative study enhances our understanding of MTD processing techniques and provides valuable references for further research and practical applications in radar signal processing and target detection systems.