The problems of joint adaptive waveform design and baseline range design for bistatic radar to maximize the practical radar resolution were considered.Distinguishing from the conventional ambiguity function(AF)-based ...The problems of joint adaptive waveform design and baseline range design for bistatic radar to maximize the practical radar resolution were considered.Distinguishing from the conventional ambiguity function(AF)-based resolution which is only related with the transmitted waveform and bistatic geometry and could be regarded as the potential resolution of a bistatic radar system,the practical resolution involves the effect of waveform,signal-to-noise ratio(SNR)as well as the measurement model.Thus,it is more practical and will have further significant application in target detection and tracking.The constraint optimization procedure of joint adaptive waveform design and baseline range design for maximizing the practical resolution of bistatic radar system under dynamic target scenario was devised.Simulation results show that the range and velocity resolution are enhanced according to the adaptive waveform and bistatic radar configuration.展开更多
To resolve problems of complicated clutter, fast-varying scenes, and low signal-clutterratio (SCR) in application of target detection on sea for space-based radar (SBR), a target detection approach based on adapti...To resolve problems of complicated clutter, fast-varying scenes, and low signal-clutterratio (SCR) in application of target detection on sea for space-based radar (SBR), a target detection approach based on adaptive waveform design is proposed in this paper. Firstly, complicated sea clutter is modeled as compound Gaussian process, and a target is modeled as some scatterers with Gaussian reflectivity. Secondly, every dwell duration of radar is divided into several sub-dwells. Regular linear frequency modulated pulses are transmitted at Sub-dwell 1, and the received signal at this sub-dwell is used to estimate clutter covariance matrices and pre-detection. Estimated matrices are updated at every following sub-dwell by multiple particle filtering to cope with fast-varying clutter scenes of SBR. Furthermore, waveform of every following sub-dwell is designed adaptively according to mean square optimization technique. Finally, principal component analysis and generalized likelihood ratio test is used for mitigation of colored interference and property of constant false alarm rate, respectively. Simulation results show that, considering configuration of SBR and condition of complicated clutter, 9 dB is reduced for SCR which reliable detection requires by this target detection approach. Therefore, the work in this paper can markedly improve radar detection performance for weak targets.展开更多
In order to improve detection and estimation performance of distributed OrthogonalFrequency-Division Multiplexing(OFDM) Multiple-Input Multiple-Output(MIMO) radar system in multi-target scene, we propose a novel a...In order to improve detection and estimation performance of distributed OrthogonalFrequency-Division Multiplexing(OFDM) Multiple-Input Multiple-Output(MIMO) radar system in multi-target scene, we propose a novel approach of Adaptive Waveform Design(AWD) based on a constrained Multi-Objective Optimization(MOO). The sparse measurement model of this radar system is derived, and the method based on decomposed Dantzig selectors is applied for the sparse recovery according to the block structures of the sparse vector and the system matrix. An AWD approach is proposed, which optimizes two objective functions, namely minimizing the upper bound of the recovery error and maximizing the weakest-target return, by adjusting the complex weights of the emitting waveform amplitudes. Several numerical simulations are provided and their results show that the detection and estimation performance of the radar system is improved significantly when this MOO-based AWD approach is applied to the distributed OFDM MIMO radar system. Especially, we verify the effectiveness of our AWD approach when the available samples are reduced severally and the technique of compressed sensing is introduced.展开更多
基金Project supported by the Program for New Century Excellent Talents in University,ChinaProject(61171133)supported by the National Natural Science Foundation of China+2 种基金Project(11JJ1010)supported by the Natural Science Fund for Distinguished Young Scholars of Hunan Province,ChinaProject(61101182)supported by the National Natural Science Foundation for Young Scientists of ChinaProject(20124307110013)supported by the Doctoral Program of Higher Education of China
文摘The problems of joint adaptive waveform design and baseline range design for bistatic radar to maximize the practical radar resolution were considered.Distinguishing from the conventional ambiguity function(AF)-based resolution which is only related with the transmitted waveform and bistatic geometry and could be regarded as the potential resolution of a bistatic radar system,the practical resolution involves the effect of waveform,signal-to-noise ratio(SNR)as well as the measurement model.Thus,it is more practical and will have further significant application in target detection and tracking.The constraint optimization procedure of joint adaptive waveform design and baseline range design for maximizing the practical resolution of bistatic radar system under dynamic target scenario was devised.Simulation results show that the range and velocity resolution are enhanced according to the adaptive waveform and bistatic radar configuration.
基金supported by the National Defense Pre-Research Foundation of China
文摘To resolve problems of complicated clutter, fast-varying scenes, and low signal-clutterratio (SCR) in application of target detection on sea for space-based radar (SBR), a target detection approach based on adaptive waveform design is proposed in this paper. Firstly, complicated sea clutter is modeled as compound Gaussian process, and a target is modeled as some scatterers with Gaussian reflectivity. Secondly, every dwell duration of radar is divided into several sub-dwells. Regular linear frequency modulated pulses are transmitted at Sub-dwell 1, and the received signal at this sub-dwell is used to estimate clutter covariance matrices and pre-detection. Estimated matrices are updated at every following sub-dwell by multiple particle filtering to cope with fast-varying clutter scenes of SBR. Furthermore, waveform of every following sub-dwell is designed adaptively according to mean square optimization technique. Finally, principal component analysis and generalized likelihood ratio test is used for mitigation of colored interference and property of constant false alarm rate, respectively. Simulation results show that, considering configuration of SBR and condition of complicated clutter, 9 dB is reduced for SCR which reliable detection requires by this target detection approach. Therefore, the work in this paper can markedly improve radar detection performance for weak targets.
基金supported by the National Basic Research Program of China(No.613205212)
文摘In order to improve detection and estimation performance of distributed OrthogonalFrequency-Division Multiplexing(OFDM) Multiple-Input Multiple-Output(MIMO) radar system in multi-target scene, we propose a novel approach of Adaptive Waveform Design(AWD) based on a constrained Multi-Objective Optimization(MOO). The sparse measurement model of this radar system is derived, and the method based on decomposed Dantzig selectors is applied for the sparse recovery according to the block structures of the sparse vector and the system matrix. An AWD approach is proposed, which optimizes two objective functions, namely minimizing the upper bound of the recovery error and maximizing the weakest-target return, by adjusting the complex weights of the emitting waveform amplitudes. Several numerical simulations are provided and their results show that the detection and estimation performance of the radar system is improved significantly when this MOO-based AWD approach is applied to the distributed OFDM MIMO radar system. Especially, we verify the effectiveness of our AWD approach when the available samples are reduced severally and the technique of compressed sensing is introduced.