Sky-wave over-the-horizon radar target and ionized layer parameter joint estimation method
A technology of over-the-horizon radar and target parameters, which is applied in the field of radar, and can solve problems such as ignoring detection equipment errors, interference, and high input signal-to-noise ratio
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Embodiment 1
[0065] Embodiment 1: Performance analysis combined with classic maximum likelihood algorithm:
[0066] Fig. 1 is the mean square error (MSE) curve of the target distance estimated by the method of the present invention (the algorithm in the figure, the same below) and the maximum likelihood (ML) algorithm respectively. Figure 2 and Figure 3 are the MSE curves of the estimated target velocity and acceleration under the same conditions. It can be seen from the figure that as the SNR increases, the MSE curve gradually decreases, and the estimation error gradually decreases. The curve of the method proposed in the present invention is significantly lower than the classic maximum likelihood method, which shows that the method is always better than the maximum likelihood method. In the case of a small ionospheric detection equipment error, the proposed method has a smaller estimation error, but because the error information of the ionosphere is not used, the parameter error of the ion...
Embodiment 2
[0067] Embodiment 2: Performance analysis combined with other target estimation algorithms
[0068] Figure 4 is the HAF and CPF methods, and the mean square error (MSE) curve of the estimated target distance improved by the method of the present invention. Figures 5 and 6 are the MSE curves of the estimated target speed and acceleration under the same conditions. It can be seen from the figure that as the SNR increases, the estimation errors of all algorithms decrease. In most cases, the CPF algorithm is better than the HAF algorithm, which is caused by the algorithm's different sensitivity to SNR. In addition, it can be found that the MSE curve applied with the method of the present invention is significantly lower than the HAF and CPF algorithms, and is equally spaced compared to the original curve, which is consistent with the theory and proves that the method proposed by the present invention is existing Further update and improvement of the algorithm can improve the estima...
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