Jamming suppression is traditionally achieved through the use of spatial filters based on array signal processing theory.In order to achieve better jamming suppression performance,many studies have applied blind sourc...Jamming suppression is traditionally achieved through the use of spatial filters based on array signal processing theory.In order to achieve better jamming suppression performance,many studies have applied blind source separation(BSS)to jamming suppression.BSS can achieve the separation and extraction of the individual source signals from the mixed signal received by the array.This paper proposes a perspective to recognize BSS as spatial band-pass filters(SBPFs)for jamming suppression applications.The theoretical derivation indicates that the processing of mixed signals by BSS can be perceived as the application of a set of SBPFs that gate the source signals at various angles.Simulations are performed using radar jamming suppression as an example.The simulation results suggest that BSS and SBPFs produce approximately the same effects.Simulation results are consistent with theoretical derivation results.展开更多
Traditional human detection using pre-trained detectors tends to be computationally intensive for time-critical tracking tasks, and the detection rate is prone to be unsatisfying when occlusion, motion blur and body d...Traditional human detection using pre-trained detectors tends to be computationally intensive for time-critical tracking tasks, and the detection rate is prone to be unsatisfying when occlusion, motion blur and body deformation occur frequently. A spatial-confidential proposal filtering method(SCPF) is proposed for efficient and accurate human detection. It consists of two filtering phases: spatial proposal filtering and confidential proposal filtering. A compact spatial proposal is generated in the first phase to minimize the search space to reduce the computation cost. The human detector only estimates the confidence scores of the candidate search regions accepted by the spatial proposal instead of global scanning. At the second phase, each candidate search region is assigned with a supplementary confidence score according to their reliability estimated by the confidential proposal to reduce missing detections. The performance of the SCPF method is verified by extensive tests on several video sequences from available public datasets. Both quantitatively and qualitatively experimental results indicate that the proposed method can highly improve the efficiency and the accuracy of human detection.展开更多
基金supported by the National Natural Science Foundation of China(6237104662201048)the Natural Science Foundation of Chongqing,China(cstc2020jcyj-msxmX0260).
文摘Jamming suppression is traditionally achieved through the use of spatial filters based on array signal processing theory.In order to achieve better jamming suppression performance,many studies have applied blind source separation(BSS)to jamming suppression.BSS can achieve the separation and extraction of the individual source signals from the mixed signal received by the array.This paper proposes a perspective to recognize BSS as spatial band-pass filters(SBPFs)for jamming suppression applications.The theoretical derivation indicates that the processing of mixed signals by BSS can be perceived as the application of a set of SBPFs that gate the source signals at various angles.Simulations are performed using radar jamming suppression as an example.The simulation results suggest that BSS and SBPFs produce approximately the same effects.Simulation results are consistent with theoretical derivation results.
基金Projects(61175096,60772063)supported by the National Natural Science Foundation of China
文摘Traditional human detection using pre-trained detectors tends to be computationally intensive for time-critical tracking tasks, and the detection rate is prone to be unsatisfying when occlusion, motion blur and body deformation occur frequently. A spatial-confidential proposal filtering method(SCPF) is proposed for efficient and accurate human detection. It consists of two filtering phases: spatial proposal filtering and confidential proposal filtering. A compact spatial proposal is generated in the first phase to minimize the search space to reduce the computation cost. The human detector only estimates the confidence scores of the candidate search regions accepted by the spatial proposal instead of global scanning. At the second phase, each candidate search region is assigned with a supplementary confidence score according to their reliability estimated by the confidential proposal to reduce missing detections. The performance of the SCPF method is verified by extensive tests on several video sequences from available public datasets. Both quantitatively and qualitatively experimental results indicate that the proposed method can highly improve the efficiency and the accuracy of human detection.
