Abstract
In this paper, performance analysis of the cross-eye jamming effect under mechanical defects is dealt with. By using a numerical analysis-based approach, the performance analysis method proposed in this paper is closer to the not approximated empirical mean square difference (MSD) than the first-order Taylor approximation-based performance analysis method and the second-order Taylor approximation-based performance analysis method proposed in previous studies. In other words, the effects of amplitude ratio perturbation and phase difference perturbation on performance degradation are quantitatively analyzed. Note that the numerical integration is adopted to derive an analytic expression of the MSD.
Highlights
The radar receives information on the target’s direction, distance, and velocity by using electromagnetic waves
Operation Time (Number of Repetitions: 3,000,000). It can be seen in Equation (3) that the jamming effect of cross-eye changes significantly due to the amplitude ratio and phase difference
The cross-eye gain is the function of amplitude ratio and phase difference
Summary
The radar receives information on the target’s direction, distance, and velocity by using electromagnetic waves. Cross eye jamming can effectively interfere with ACM’s angular tracking by changing the value of the received sum and difference of the ACM sensor [3,4,5,6,7]. The jamming signal generated by the cross-eye’s jammer antenna changes the sum of reception of the ACM and the value of the difference, causing an angle error [3,4,5,6,7,8,9,10]. To get an analytic expression of the mean square difference (MSD), the Taylor approximation should be applied to the cross-eye gain expression. In order to improve the accuracy of the MSD calculation, we propose a numerical integration-based MSD of cross-eye gain. We improve the MSD calculation accuracy of the cross-eye gain by considering the perturbation through numerical integration-based method. In the conclusion, we summarize the overall contents of this paper and emphasize the advantages of the numerical integration-based MSD method compared to Monte-Carlo simulationbased MSD and analytic-based approximated MSD
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