Title
Waveform Optimization for Target Scattering Coefficients Estimation Under Detection and Peak-to-Average Power Ratio Constraints in Cognitive Radar.
Abstract
This work investigates the estimation of target scattering coefficients (TSC) in cognitive radar systems with temporally correlated targets. An estimation method based on Kalman filtering (KF) is proposed to exploit the temporal TSC correlation between the pulses in the frequency domain. To minimize the mean square error of the estimated TSC at each KF iteration, unlike existing indirect methods, in this paper the radar waveform is optimized directly under the constraints of transmitted power, peak-to-average power ratio (PAPR) and detection probability. Since the optimization problem regarding the waveform design is non-convex, a novel method is proposed to convert this problem into a convex one. Simulation results demonstrate that the performance of the TSC estimation for the temporally correlated target is significantly improved by radar waveform optimization. Meanwhile, no performance degradation is observed with the introduction of the additional PAPR constraints and the detection constraints for KF estimation with the optimized waveform.
Year
DOI
Venue
2016
10.1007/s00034-015-0048-y
Circuits Systems and Signal Processing
Keywords
Field
DocType
Cognitive radar system, Detection probability, Kalman filtering, PAPR, Radar waveform optimization
Frequency domain,Mathematical optimization,Control theory,Waveform,Mean squared error,Regular polygon,Kalman filter,Scattering,Optimization problem,Mathematics,Cognitive radar
Journal
Volume
Issue
ISSN
35
1
1531-5878
Citations 
PageRank 
References 
1
0.35
8
Authors
3
Name
Order
Citations
PageRank
Peng Chen1344.28
Lenan Wu270062.18
Chenhao Qi320926.34