Hypothesis-testing-based Range Statistical Resolution Limit of Radar
ZHANG Yunlei①② TANG Jun①* WANG Li①
①(Department of Electronic Engineering, Tsinghua University, Beijing 100084, China) ②(Institute of Electronic Engineering, Navy University of Engineering, Wuhan 430033, China)
Abstract Resolution performance is an important performance criteria of the radar systems. Typically, the Ambiguity Function (AF) of signals is used to define the range and Doppler limits. In this study Some new opinions are proposed-First, the AF is based on the signals processed with matched filter, which can guarantee the maximization of the output of the Signal-to-Noise Ratio (SNR). Thus, the AF is optimal for target detection. However, the AF is unsuitable for the resolution of multiple targets. Second, the AF cannot reflect the effect of random factors, such as noise, target fluctuation, and mutual interference of close targets. Third, the AF can only handle two equal-powered targets and provide the conclusion of the limits. However, the AF fails to distinguish multiple unequal-powered targets, which is often the case in reality. Therefore, the hypothesis testing theory is applied to resolve the range resolution of two closely spaced targets for radars, and our study is based on the original echoes of the signals. With the definition of the correct resolution and false alarm rates in the statistical standpoint, we derive the expression of the range Statistical Resolution Limit (SRL). The simulation results indicate that the SRL can exceed the Rayleigh limit. With the false alarm and correct resolution rates being 0.001 and 0.5, respectively, for the two uncorrelated-amplitude linear-frequency-modulated signals, the range SRL can be as low as 0.3 times of the Rayleigh limit.
Fund: The National Key Research and Development Program of China (2016YFA0302102), The National Natural Science Foundation of China under Grant (61501486)
Cite this article:
ZHANG Yunlei,TANG Jun,WANG Li. Hypothesis-testing-based Range Statistical Resolution Limit of Radar[J]. JOURNAL OF RADARS, 2018, 0(0): 0-0.
2018, Vol. 0 