Gravity/inertial combination navigation is a leading issue in realizing passive navigation onboard a submarine. A new rotation-fitting gravity matching algorithm, based on the Terrain Contour Matching (TERCOM) algorit...Gravity/inertial combination navigation is a leading issue in realizing passive navigation onboard a submarine. A new rotation-fitting gravity matching algorithm, based on the Terrain Contour Matching (TERCOM) algorithm, is proposed in this paper. The algorithm is based on the principle of least mean-square-error criterion, and searches for a certain matched trajectory that runs parallel to a trace indicated by an inertial navigation system on a gravity base map. A rotation is then made clockwise or counterclockwise through a certain angle around the matched trajectory to look for an optimal matched trajectory within a certain angle span range, and through weighted fitting with another eight suboptimal matched trajectories, the endpoint of the fitted trajectory is considered the optimal matched position. In analysis of the algorithm reliability and matching error, the results from simulation indicate that the optimal position can be obtained effectively in real time, and the positioning accuracy improves by 35% and up to 1.05 nautical miles using the proposed algorithm compared with using the widely employed TERCOM and SITAN methods. Current gravity-aided navigation can benefit from implementation of this new algorithm in terms of better reliability and positioning accuracy.展开更多
In this paper,average bit error probability(ABEP)bound of optimal maximum likelihood(ML)detector is first derived for ultra massive(UM)multiple-input-multiple-output(MIMO)system with generalized amplitude phase modula...In this paper,average bit error probability(ABEP)bound of optimal maximum likelihood(ML)detector is first derived for ultra massive(UM)multiple-input-multiple-output(MIMO)system with generalized amplitude phase modulation(APM),which is confirmed by simulation results.Furthermore,a minimum residual criterion(MRC)based lowcomplexity near-optimal ML detector is proposed for UM-MIMO system.Specifically,we first obtain an initial estimated signal by a conventional detector,i.e.,matched filter(MF),or minimum mean square error(MMSE)and so on.Furthermore,MRC based error correction mechanism(ECM)is proposed to correct the erroneous symbol encountered in the initial result.Simulation results are shown that the performance of the proposed MRC-ECM based detector is capable of approaching theoretical ABEP of ML,despite only imposing a slightly higher complexity than that of the initial detector.展开更多
基金supported by National Natural Science Foundation of China (Grant Nos. 41074051, 41021003 and 40874037)
文摘Gravity/inertial combination navigation is a leading issue in realizing passive navigation onboard a submarine. A new rotation-fitting gravity matching algorithm, based on the Terrain Contour Matching (TERCOM) algorithm, is proposed in this paper. The algorithm is based on the principle of least mean-square-error criterion, and searches for a certain matched trajectory that runs parallel to a trace indicated by an inertial navigation system on a gravity base map. A rotation is then made clockwise or counterclockwise through a certain angle around the matched trajectory to look for an optimal matched trajectory within a certain angle span range, and through weighted fitting with another eight suboptimal matched trajectories, the endpoint of the fitted trajectory is considered the optimal matched position. In analysis of the algorithm reliability and matching error, the results from simulation indicate that the optimal position can be obtained effectively in real time, and the positioning accuracy improves by 35% and up to 1.05 nautical miles using the proposed algorithm compared with using the widely employed TERCOM and SITAN methods. Current gravity-aided navigation can benefit from implementation of this new algorithm in terms of better reliability and positioning accuracy.
基金supported in part by the National Key Research and Development Program of China under Grant 2019YFB1803400in part by the National Science Foundation of China under Grant 62001179in part by the Fundamental Research Funds for the Central Universities under Grant 2020kfyXJJS111.
文摘In this paper,average bit error probability(ABEP)bound of optimal maximum likelihood(ML)detector is first derived for ultra massive(UM)multiple-input-multiple-output(MIMO)system with generalized amplitude phase modulation(APM),which is confirmed by simulation results.Furthermore,a minimum residual criterion(MRC)based lowcomplexity near-optimal ML detector is proposed for UM-MIMO system.Specifically,we first obtain an initial estimated signal by a conventional detector,i.e.,matched filter(MF),or minimum mean square error(MMSE)and so on.Furthermore,MRC based error correction mechanism(ECM)is proposed to correct the erroneous symbol encountered in the initial result.Simulation results are shown that the performance of the proposed MRC-ECM based detector is capable of approaching theoretical ABEP of ML,despite only imposing a slightly higher complexity than that of the initial detector.
