Weak Target Detection Method of Passive Bistatic Radar Based on Probability Histogram

Abstract

Passive bistatic radar (PBR) has attracted widespread attention for its capabilities in dealing with the threat of electronic countermeasure, stealth technology, and antiradiation missile. However, passive detection methods are limited by unknown characteristics of the uncooperative illuminators, and conventional radar signal processing algorithms cannot be conducted accurately, especially when the carrier frequency of the transmitting signal is agile and the signal-to-noise ratio (SNR) in the scattered wave of target is low. To address the above problems, this paper presents a novel weak target detection method based on probability histogram, which is then tested by a field experiment. Preliminary results indicate the feasibility of the proposed method in weak target detection.

DOA Estimation Method in Multipath Environment for Passive Bistatic Radar

“…Meanwhile, a frequency agile phased array VHF radar is used as the uncooperative illuminator of opportunity. Refer to analysis in [10]; the frequency agility technology can increase the ability of antijamming and increase the detection probability. The phased array technology provides flexible beam pattern, angular diversity, and more degrees of freedom, which makes it competent for the task of detecting and tracking different targets.…”

“…Compared with the aforementioned illuminators of opportunity, a dedicated radar usually has high power and an idea ambiguity function. In recent years, frequency agility and phased array technology are widely used in very high frequency (VHF) radar systems for remote sensing and surveillance purpose because it provides flexible beam scanning, improved detection probability, and high valuable counter to stealth technology [10,11]. The use of frequency agile phased array VHF radar can extend the range of available illuminators of opportunity, while it also poses many challenges in PBR signal processing, such as low signal-to-noise ratio (SNR), limited snapshots, etc.…”

Likelihood function modelling of radar targets under high‐speed observation

“…Improving detection performance by effectively utilizing raw data information is the most direct and low-cost method to enhance the efficacy of radar systems. Thus, weak target detection has become a crucial research problem in radar signal processing [1][2][3][4][5][6][7]. Conventional detection algorithms construct likelihood ratio functions using Gaussian models [8][9][10][11] or random undulation models [12,13].…”