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.