A joint estimation method of sky-wave over-the-horizon radar target and ionospheric parameters
An over-the-horizon radar and target parameter technology, applied in the radar field, can solve problems such as low estimation accuracy, ignoring detection equipment errors, and high input signal-to-noise ratio
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Embodiment 1
[0065] Embodiment 1: Performance analysis combined with classical maximum likelihood algorithm:
[0066] figure 1 is the mean square error (MSE) curve of the target distance estimated by the method of the present invention (the algorithm in this paper in the figure, the same below) and the maximum likelihood (ML) algorithm respectively. figure 2 with image 3 are the MSE curves of the estimated target velocity and acceleration under the same conditions, respectively. 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 by the present invention is obviously lower than that of the classic maximum likelihood method, which shows that the method is always better than the maximum likelihood method. In the case of small ionospheric detection equipment error, the estimation error of the proposed method is smaller, but because the error information of the ionospher...
Embodiment 2
[0067] Example 2: Performance Analysis Jointly with Other Target Estimation Algorithms
[0068] Figure 4 are the HAF and CPF methods, and the mean square error (MSE) curve of the target distance estimated after the improvement of the method of the present invention. Figure 5 with Image 6 are the MSE curves of the estimated target velocity and acceleration under the same conditions, respectively. It can be seen from the figure that as the SNR increases, the estimation errors of all algorithms decrease. Most of the time, the CPF algorithm is better than the HAF algorithm, which is due to the different sensitivity of the algorithm to the SNR. In addition, it can be found that the MSE curve using the method of the present invention is significantly lower than that of the HAF and CPF algorithms, and is equally spaced compared to the original curve, which is consistent with the theory and proves that the proposed method of the present invention is an existing The further upda...
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