The block-diagonal least squares method, which theoretically has specific requirements for the observation data and the spatial distribution of its precision, plays an important role in ultra-high degree gravity field...The block-diagonal least squares method, which theoretically has specific requirements for the observation data and the spatial distribution of its precision, plays an important role in ultra-high degree gravity field determination. On the basis of block-diagonal least squares method, three data processing strategies are employed to determine the gravity field models using three kinds of simulated global grid data with different noise spatial distri- bution in this paper. The numerical results show that when we employed the weight matrix corresponding to the noise of the observation data, the model computed by the least squares using the full normal matrix has much higher precision than the one estimated only using the block part of the normal matrix. The model computed by the block-diagonal least squares method without the weight matrix has slightly lower precision than the model computed using the rigorous least squares with the weight matrix. The result offers valuable reference to the using of block-diagonal least squares method in ultra-high gravity model determination.展开更多
Distributed precision jamming(DPJ)is a novel blanket jamming concept in electronic warfare,which delivers the jamming resource to the opponent equipment precisely and ensures that friendly devices are not affected.Rob...Distributed precision jamming(DPJ)is a novel blanket jamming concept in electronic warfare,which delivers the jamming resource to the opponent equipment precisely and ensures that friendly devices are not affected.Robust jamming performance and low hardware burden on the jammers are crucial for practical DPJ implementation.To achieve these goals,we study the robust design of wideband constant modulus(CM)discrete phase waveform for DPJ,where the worst-case combined power spectrum(CPS)of both the opponent and friendly devices is considered in the objective function,and the CM discrete phase constraints are used to design the wideband waveform.Specifically,the resultant mathematical model is a large-scale minimax multi-objective optimization problem(MOP)with CM and discrete phase constraints.To tackle the challenging MOP,we transform it into a single-objective minimization problem using the Lp-norm and Pareto framework.For the approximation problem,we propose the Riemannian conjugate gradient for CM discrete phase constraints(RCG-CMDPC)algorithm with low computational complexity,which leverages the complex circle manifold and a projection method to satisfy the CM discrete phase constraints within the RCG framework.Numerical examples demonstrate the superior robust DPJ effectiveness and computational efficiency compared to other competing algorithms.展开更多
基金supported by the National Natural Science Foundation of China for Distinguished Young Scholars (41404028)
文摘The block-diagonal least squares method, which theoretically has specific requirements for the observation data and the spatial distribution of its precision, plays an important role in ultra-high degree gravity field determination. On the basis of block-diagonal least squares method, three data processing strategies are employed to determine the gravity field models using three kinds of simulated global grid data with different noise spatial distri- bution in this paper. The numerical results show that when we employed the weight matrix corresponding to the noise of the observation data, the model computed by the least squares using the full normal matrix has much higher precision than the one estimated only using the block part of the normal matrix. The model computed by the block-diagonal least squares method without the weight matrix has slightly lower precision than the model computed using the rigorous least squares with the weight matrix. The result offers valuable reference to the using of block-diagonal least squares method in ultra-high gravity model determination.
基金supported by the National Natural Science Foundation of China(No.62301581)the Postgraduate Scientific Research Innovation Project of Hunan Province,China(No.CX20230045)。
文摘Distributed precision jamming(DPJ)is a novel blanket jamming concept in electronic warfare,which delivers the jamming resource to the opponent equipment precisely and ensures that friendly devices are not affected.Robust jamming performance and low hardware burden on the jammers are crucial for practical DPJ implementation.To achieve these goals,we study the robust design of wideband constant modulus(CM)discrete phase waveform for DPJ,where the worst-case combined power spectrum(CPS)of both the opponent and friendly devices is considered in the objective function,and the CM discrete phase constraints are used to design the wideband waveform.Specifically,the resultant mathematical model is a large-scale minimax multi-objective optimization problem(MOP)with CM and discrete phase constraints.To tackle the challenging MOP,we transform it into a single-objective minimization problem using the Lp-norm and Pareto framework.For the approximation problem,we propose the Riemannian conjugate gradient for CM discrete phase constraints(RCG-CMDPC)algorithm with low computational complexity,which leverages the complex circle manifold and a projection method to satisfy the CM discrete phase constraints within the RCG framework.Numerical examples demonstrate the superior robust DPJ effectiveness and computational efficiency compared to other competing algorithms.
