The low-angle tracking in multipath interference is a challenging problem for the Very High Frequency(VHF)radar.The colocated Multi-Input Multi-Output(MIMO)technique can remedy such a defect.In this paper,a Joint Beam...The low-angle tracking in multipath interference is a challenging problem for the Very High Frequency(VHF)radar.The colocated Multi-Input Multi-Output(MIMO)technique can remedy such a defect.In this paper,a Joint Beam-Target Assignment and Power Allocation(JBTAPA)strategy is proposed for the VHF-MIMO radar network tracking low-angle targets.The core of the JBTAPA strategy is to improve the worst tracking accuracy among multiple targets by assigning appropriate beams to targets and allocating the power resource in each beam using the feedback information in the tracking cycle.Taking into account the transmit multipath and receive multipath,we derive the Cramer-Rao Lower Bound(CRLB)on angle estimate,which is then incor-porated in the Predicted Conditional CRLB(PC-CRLB).A more accurate and consistent lower bound is provided as the optimization metric since the PC-CRLB is based on the most recently real-ized measurements.A two-stage-based technique is proposed to solve the JBTAPA problem,which is originally NP-hard.Simulation results verify the effectiveness and efficiency of the proposed method.The results also imply that the target reflectivity plays one of the important roles in resource allocation.展开更多
The resource optimization plays an important role in an asynchronous Phased Array Radar Network(PARN)tracking multiple targets with Measurement Origin Uncertainty(MOU),i.e.,considering the false alarms and missed dete...The resource optimization plays an important role in an asynchronous Phased Array Radar Network(PARN)tracking multiple targets with Measurement Origin Uncertainty(MOU),i.e.,considering the false alarms and missed detections.A Joint Dwell Time Allocation and Detection Threshold Optimization(JDTADTO)strategy is proposed for resource saving in this case.The Predicted Conditional Cramér-Rao Lower Bound(PC-CRLB)with Bayesian Detector and Amplitude Information(BD-AI)is derived and adopted as the tracking performance metric.The optimization model is formulated as minimizing the difference between the PC-CRLBs and the tracking precision thresholds under the constraints of upper and lower bounds of dwell time and false alarm ratio.It is shown that the objective function is nonconvex due to the Information Reduction Factor(IRF)brought by the MOU.A cyclic minimizer-based solution is proposed for problem solving.Simulation results confirm the flexibility and robustness of the JDTADTO strategy in both sufficient and insufficient resource scenarios.The results also reveal the effectiveness of the proposed strategy compared with the strategies adopting the BD without detection threshold optimization and amplitude information.展开更多
基金supported by the National Nature Science Foundation of China(No.62001506).
文摘The low-angle tracking in multipath interference is a challenging problem for the Very High Frequency(VHF)radar.The colocated Multi-Input Multi-Output(MIMO)technique can remedy such a defect.In this paper,a Joint Beam-Target Assignment and Power Allocation(JBTAPA)strategy is proposed for the VHF-MIMO radar network tracking low-angle targets.The core of the JBTAPA strategy is to improve the worst tracking accuracy among multiple targets by assigning appropriate beams to targets and allocating the power resource in each beam using the feedback information in the tracking cycle.Taking into account the transmit multipath and receive multipath,we derive the Cramer-Rao Lower Bound(CRLB)on angle estimate,which is then incor-porated in the Predicted Conditional CRLB(PC-CRLB).A more accurate and consistent lower bound is provided as the optimization metric since the PC-CRLB is based on the most recently real-ized measurements.A two-stage-based technique is proposed to solve the JBTAPA problem,which is originally NP-hard.Simulation results verify the effectiveness and efficiency of the proposed method.The results also imply that the target reflectivity plays one of the important roles in resource allocation.
基金supported by the National Natural Science Foundation of China(Nos.62001506 and 62071482).
文摘The resource optimization plays an important role in an asynchronous Phased Array Radar Network(PARN)tracking multiple targets with Measurement Origin Uncertainty(MOU),i.e.,considering the false alarms and missed detections.A Joint Dwell Time Allocation and Detection Threshold Optimization(JDTADTO)strategy is proposed for resource saving in this case.The Predicted Conditional Cramér-Rao Lower Bound(PC-CRLB)with Bayesian Detector and Amplitude Information(BD-AI)is derived and adopted as the tracking performance metric.The optimization model is formulated as minimizing the difference between the PC-CRLBs and the tracking precision thresholds under the constraints of upper and lower bounds of dwell time and false alarm ratio.It is shown that the objective function is nonconvex due to the Information Reduction Factor(IRF)brought by the MOU.A cyclic minimizer-based solution is proposed for problem solving.Simulation results confirm the flexibility and robustness of the JDTADTO strategy in both sufficient and insufficient resource scenarios.The results also reveal the effectiveness of the proposed strategy compared with the strategies adopting the BD without detection threshold optimization and amplitude information.
