Low-Altitude and Slow-Speed Small Target Detection Based on Spectrum Zoom Processing

Abstract

This paper proposes a spectrum zoom processing based target detection algorithm for detecting the weak echo of low-altitude and slow-speed small (LSS) targets in heavy ground clutter environments, which can be used to retrofit the existing radar systems. With the existing range-Doppler frequency images, the proposed method firstly concatenates the data from the same Doppler frequency slot of different images and then applies the spectrum zoom processing. After performing the clutter suppression, the target detection can be finally implemented. Through the theoretical analysis and real data verification, it is shown that the proposed algorithm can obtain a preferable spectrum zoom result and improve the signal-to-clutter ratio (SCR) with a very low computational load.

Applications of Fractional Lower Order Frequency Spectrum Technologies to Bearing Fault Analysis

“…The traditional spectrum estimation methods mainly include Blackman-Tukey (BT), Periodogram, Welch, multiple signal classification, wavelet spectrum, and parameter model spectrum estimation. The spectral analysis methods have been widely applied in radar signal processing [1], passive sonar signal processing [2], target recognition [3], seismic analysis [4], mechanical failure analysis, and other fields [5][6][7]. Recently, some improved methods were also applied to machine breakdown analysis, such that singular spectrum analysis was used for roller element bearing fault diagnosis [8,9].…”