A Study For Digital Pulse Compression Algorithms With Low Range Sidelobe On Pulse Radar

Radar is an important targets detection equipment when the targets are on the sea or on the ground other or in the space or the sky. According to the wave form that radar emits, it is divided into continuous wave radar(CWR) and pulse radar(PR). The CWR, whose emitting antenna and receiving antenna are separated, emits electromagnetic wave continuously, and it surveys the target’s radial velocity and direction. The PR, in which the controlling-time device controls the time that radar emits electromagnetic wave and receives the echo, and the duplex device controls the antenna conversion between emission and receive. Radar emits the modulated pulse wave, and extracts the range information from the radar echo.In the PR system, in order to enlarge detected range, it is necessary to raise the mean power that radar emits signal, which force people to emit wide pulse signal. However, the wide pulse echo brings the range resolution degrade, which will makes the very near targets not departed. A technique to solve the problem that targets are difficult to be departed is pulse compression, whose primary method is that the received echo pulse width is made to become narrower, which will raise the range resolution and depart those close targets. In modern radar system, digital pulse compression is disposed by DSP, one advantage of which is that it is easy to get good performance of depressing sidelobe only by improving the inner PC algorithms.Therefore, in this paper we focus on researching digital pulse compression algorithms with low range sidelobe on pulse radar, and solve two key problems in digital pulse compression, one is to improve convolution-based PC algorithms to make their range sidelobe lower and these method more practical, the other is to realize deconvolution-based PC algorithms and low range sidelobe. In the respect of realizing the convolution-based PC with low range sidelobe, we study window functions, their performance and windowing technology, choose those window functions that can have low range sidelobe, improve windowing technology, and realize ultra-low sidelobe PC. In respect of realizing the deconvolution-based PC with low range sidelobe, we study the performance of several deconvolution algorithms, choose those deconvolution algorithms and apodization algorithms with good performance to do digital PC. Finally, we compare these two kinds of digital PC algorithms from their primary, input signals, reference signals, output signals, finish digital PC by simulated LFM signal, study their PC effectiveness at different SNR. All this we do can provide a reference for PR to choose a proper digital PC algorithm in executing PC.