A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance(LCMV)criterion for adaptive monopulse systems is proposed.The weight vector associated with the original...A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance(LCMV)criterion for adaptive monopulse systems is proposed.The weight vector associated with the original whole antenna array is decomposed into several adaptive weight sub-vectors firstly.An adaptive algorithm based on the conventional LCMV principle is then deduced to update the weight sub-vectors for sum and difference beam,respectively.The optimal weight vector can be obtained after convergence.The required computational complexity is evaluated for the proposed technique,which is on the order of O(N)and less than that of the conventional LCMV method.The flow chart scheme with the partial parallel structure of the proposed algorithm is introduced.This scheme is easy to be implemented on a distributed computer/digital signal processor(DSP)system to solve the problems of the heavy computational burden and vast data transmission of the large-scale adaptive monopulse array.Then,the monopulse ratio and convergence rate of the proposed algorithm are evaluated by numerical simulations.Compared with some recent adaptive monopulse estimation methods,a better performance on computational complexity and monopulse ratio can be achieved with the proposed adaptive method.展开更多
For a large-scale adaptive array, the heavy computational load and the high-rate data transmission are two challenges in the implementation of an adaptive digital beamforming system. An efficient parallel digital beam...For a large-scale adaptive array, the heavy computational load and the high-rate data transmission are two challenges in the implementation of an adaptive digital beamforming system. An efficient parallel digital beamforming （DBF） algorithm based on the least mean square algorithm （PLMS） is proposed. An appropriate method is found to partition the least mean square （LMS） algorithm into a number of operational modules, which can be easily executed in a distributed-parallel-processing fashion. As a result, the proposed PLMS algorithm provides an effective solution that can alleviate the bottleneck of high-rate data transmission and reduce the computational cost. PLMS requires less computational load than that of the conventional parallel algorithms based on the recursive least square （RLS） algorithm, as well as it is easier to be implemented to do real time adaptive array processing. Moreover, low sidelobe of the beam pattern is obtained by constraining the static steering vector with Tschebyscheff coefficients. Finally, a scheme of the PLMS algorithm using distributed-parallel-processing system is also proposed. The simulation results demonstrate that the PLMS algorithm has the same interference cancellation performance as that of the conventional LMS algorithm. Moreover, the PLMS algorithm can obtain the same good beamforming performance, regardless how the algorithm is partitioned. It is expected that the proposed algorithm will be used in a large-scale adaptive array system to deal with real time adaptive digital beamforming processing.展开更多
L波段数字航空通信系统(L-band digital aeronautical communication system,LDACS)作为未来航空数据链的重要技术手段之一,非常容易受到相邻波道的测距机系统信号的干扰。为此,提出一种基于稀疏贝叶斯推断的LDACS波束形成方法。首先,将...L波段数字航空通信系统(L-band digital aeronautical communication system,LDACS)作为未来航空数据链的重要技术手段之一,非常容易受到相邻波道的测距机系统信号的干扰。为此,提出一种基于稀疏贝叶斯推断的LDACS波束形成方法。首先,将LDACS地面站的粗略来向信息作为先验,并根据空域信号来向的稀疏性构建稀疏信号。随后,通过贝叶斯推断估算干扰和噪声的功率,估计各个信源的来向。最后,重构干扰噪声协方差矩阵,获得波束形成权矢量。该方法无需知晓干扰数量、干扰来向等信息。仿真结果表明,该方法在低信噪比和少快拍条件下也能稳定输出波束方向图,表现出较好性能。展开更多
基金supported by the National Natural Science Foundation of China(11273017)
文摘A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance(LCMV)criterion for adaptive monopulse systems is proposed.The weight vector associated with the original whole antenna array is decomposed into several adaptive weight sub-vectors firstly.An adaptive algorithm based on the conventional LCMV principle is then deduced to update the weight sub-vectors for sum and difference beam,respectively.The optimal weight vector can be obtained after convergence.The required computational complexity is evaluated for the proposed technique,which is on the order of O(N)and less than that of the conventional LCMV method.The flow chart scheme with the partial parallel structure of the proposed algorithm is introduced.This scheme is easy to be implemented on a distributed computer/digital signal processor(DSP)system to solve the problems of the heavy computational burden and vast data transmission of the large-scale adaptive monopulse array.Then,the monopulse ratio and convergence rate of the proposed algorithm are evaluated by numerical simulations.Compared with some recent adaptive monopulse estimation methods,a better performance on computational complexity and monopulse ratio can be achieved with the proposed adaptive method.
文摘For a large-scale adaptive array, the heavy computational load and the high-rate data transmission are two challenges in the implementation of an adaptive digital beamforming system. An efficient parallel digital beamforming （DBF） algorithm based on the least mean square algorithm （PLMS） is proposed. An appropriate method is found to partition the least mean square （LMS） algorithm into a number of operational modules, which can be easily executed in a distributed-parallel-processing fashion. As a result, the proposed PLMS algorithm provides an effective solution that can alleviate the bottleneck of high-rate data transmission and reduce the computational cost. PLMS requires less computational load than that of the conventional parallel algorithms based on the recursive least square （RLS） algorithm, as well as it is easier to be implemented to do real time adaptive array processing. Moreover, low sidelobe of the beam pattern is obtained by constraining the static steering vector with Tschebyscheff coefficients. Finally, a scheme of the PLMS algorithm using distributed-parallel-processing system is also proposed. The simulation results demonstrate that the PLMS algorithm has the same interference cancellation performance as that of the conventional LMS algorithm. Moreover, the PLMS algorithm can obtain the same good beamforming performance, regardless how the algorithm is partitioned. It is expected that the proposed algorithm will be used in a large-scale adaptive array system to deal with real time adaptive digital beamforming processing.
文摘L波段数字航空通信系统(L-band digital aeronautical communication system,LDACS)作为未来航空数据链的重要技术手段之一,非常容易受到相邻波道的测距机系统信号的干扰。为此,提出一种基于稀疏贝叶斯推断的LDACS波束形成方法。首先,将LDACS地面站的粗略来向信息作为先验,并根据空域信号来向的稀疏性构建稀疏信号。随后,通过贝叶斯推断估算干扰和噪声的功率,估计各个信源的来向。最后,重构干扰噪声协方差矩阵,获得波束形成权矢量。该方法无需知晓干扰数量、干扰来向等信息。仿真结果表明,该方法在低信噪比和少快拍条件下也能稳定输出波束方向图,表现出较好性能。
