Abstract
Detection of a noisy signal is a complex process. Many radar systems are working in an environment where the signal processing parts cannot overcome the effects of interference sources due to their high power. These sources of conflict may completely erode the signal or may make a mistake in deciding. It may make the return of the echoes of the goals difficult. To solve this problem, the detector processor can use a new algorithm to estimate noise power and then can set the threshold in different positions of the cell under test. The proposed algorithm, by differentiating between homogeneous and interference environments in a multitarget structure, selects a set of reference cells that surround the cell under test to estimate the unknown noise/clutter and determine the effective threshold. Then, to evaluate the performance of cell averaging of constant false alarm rate (CA-CFAR), censored mean level detector CFAR (CMLD-CFAR), and excision CFAR (EX-CFAR) detectors, we compared threshold, false alarm, and detection probability in terms of different correlation coefficients. The values were obtained using simulation by MATLAB software. The simulation results show that the excision parameter, by adding to the window of the reference cells that surround the cell under test, reduces the effects of background noise on the received signal. We conclude from the proposed method that the hybrid detector not only has higher quality detection interactions in heterogeneous environments but also has relatively less computational complexity than CA-CFAR, CMLD-CFAR, and EX-CFAR detectors.
Highlights
The accurate detection of targets in the presence of clutter is an issue of importance to radar systems, which is, the most important destructive factor in detecting moving targets
It is clear from the results that the performance of this detector in similar conditions does not change much compared to the cell averaging of constant false alarm rate (CA-Constant false alarm rate (CFAR)) detector
The created parameter has been used to determine the standard for the censoring of abnormal values in the reference cell
Summary
The accurate detection of targets in the presence of clutter is an issue of importance to radar systems, which is, the most important destructive factor in detecting moving targets. The conventional method for using CFAR theory is to estimate the range of ambient interference with range cells and to determine the threshold level for detecting false alarm probability. Farrouki introduced the greatest of statistical CFAR (GS-CFAR) method based on an automatic censoring technique [13] Another group of researchers combined the benefits of different approaches to obtain a better assessment function [14,15,16]. This test combines an innovative solution with the OS called cell index CFAR (CI-CFAR) In this combination method, the probability of false alarms and the likelihood of a change is altered when the number of disturbing signals changes randomly.
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