利用GPS实现高轨卫星定位的抗远近效应算法

针对GPS应用于高轨卫星定位面临的远近效应问题, 提出利用正交相关的联合极大似然估计算法来对GPS信号进行二维搜索, 可以得到正确的码延时及多普勒估计. 极大似然估计算法首先利用滑行相关法对仿真信号中的强信号进行搜索, 得到强信号模型, 然后利用正交相关去掉强信号, 最终实现对弱信号的正确捕获. 本文对高轨卫星接收到的GPS信号进行了功率分析, 并建立了信号模型, 进行了算法仿真. 结果表明, 这种估计算法能够提高二维搜索性能, 有效解决远近效应问题. 

Solving the Near-far Problem for Positioning the High Earth Orbital Satellite With GPS

Cross correlations caused by the limited dynamic range of the GPS Gold codes represent a significant "near-far" problem when GPS is used for positioning of High Earth Orbital (HEO) satellite. The power differences among signals received by High Earth Orbital satellite from different GPS satellites will be up to tens of dB since the lobe amplitude of GPS satellite transmit antenna and transmission distance are both different. Based on the requirement of positioning of HEO satellite using GPS, a Maximum Likelihood (ML) estimator algorithm is used to resolve the near-far problem introduced by the sub-optimal sliding correlator solution. The GPS maximum likelihood estimator acquisition algorithm performs a simultaneous, two-dimensional search of both the Doppler frequencies and GPS Gold codes. At first, simple cross correlator is used to detect the strong code signal. Then, a fine acquisition will be done to estimate the parameters of the strong code signal accurately. The maximum likelihood algorithm is used to cancel the strong code signal. As the near-far problem has been dealt with by canceling the strong code signal, the acquisition of the weak code signal can still be completed. In order to show the good performance of the estimator,GPS signal received by HEO satellite is analyzed to generate a simulated signal. Also, simulations have been done to compare the performance of the maximum likelihood estimator and the Simple Correlator (SC) algorithm. The result shows that the maximum likelihood estimator can improve the two-dimensional searching performance and decrease the interference arising from near-far problem.