This paper presents a new algorithm based on the power inversion （PI） and the linearly constrained minimum variance （LCMV）. This algorithm is capable of adjusting the weights of the antenna array in real time to r...This paper presents a new algorithm based on the power inversion （PI） and the linearly constrained minimum variance （LCMV）. This algorithm is capable of adjusting the weights of the antenna array in real time to respond to and improve the global positioning system （GPS） received signals coming from the desired directions and at the same time to highly suppress the jammers coming from the other directions. The simulation is performed for fixed and moving jammers. It indicates that this structure can give deeper nulls, more than 115 dB depths for fixed jammers and more than 94 dB depths for moving jammers.展开更多
The convergence rate of the power inversion （PI） algorithm is quite sensitive to the power of the interference with the used fixed parameters in the PI algorithm leading to degradation of its ability to handle inter...The convergence rate of the power inversion （PI） algorithm is quite sensitive to the power of the interference with the used fixed parameters in the PI algorithm leading to degradation of its ability to handle interference. This paper presents a normalized PI algorithm that traces the stochastic characteristics of the interference. The algorithm adaptively adjusts the recursive step size to determine the constrained optimized parameters for the Iowpass filter. Simulations show that the normalized PI algorithm achieves faster convergence and produces deeper nulls. The algorithm makes GPS receivers more robust in environments with large variations in the interference strength.展开更多
文摘This paper presents a new algorithm based on the power inversion （PI） and the linearly constrained minimum variance （LCMV）. This algorithm is capable of adjusting the weights of the antenna array in real time to respond to and improve the global positioning system （GPS） received signals coming from the desired directions and at the same time to highly suppress the jammers coming from the other directions. The simulation is performed for fixed and moving jammers. It indicates that this structure can give deeper nulls, more than 115 dB depths for fixed jammers and more than 94 dB depths for moving jammers.
基金Supported by the National High-Tech Research and Development(863) Program of China (No. 2006AA701108)
文摘The convergence rate of the power inversion （PI） algorithm is quite sensitive to the power of the interference with the used fixed parameters in the PI algorithm leading to degradation of its ability to handle interference. This paper presents a normalized PI algorithm that traces the stochastic characteristics of the interference. The algorithm adaptively adjusts the recursive step size to determine the constrained optimized parameters for the Iowpass filter. Simulations show that the normalized PI algorithm achieves faster convergence and produces deeper nulls. The algorithm makes GPS receivers more robust in environments with large variations in the interference strength.
