Double Truncated Singular Value Estimation Based on Signal-to-Noise Ratio Test

A double truncated singular value estimation based on signal-to-noise ratio test is proposed by combining the measurement results of the harm degree that complex common linear exerts on parameter estimation and the truncated singular value decomposition(TSVD) estimation. Based on the signal to noise ratio(SNR) test, all the parameters are divided into two parts, according to the estimated SNR value of each parameter's least square estimation. The TSVD estimation of these two parts is truncated at different intensities. We choose a smaller truncated parameter for parameters which suffer more from complex common linear, and a bigger truncated parameter for parameters which suffer less from complex common linear, thus minimize the deviation and reduce the variance of parameter estimation effectively. This new method is applied to the simulation example of the GEO satellite orbit determination. The experimental results show that the new method is more accurate.