Title
Cognitive Design of Radar Waveform and the Receive Filter for Multitarget Parameter Estimation
Abstract
This research work considers waveform design for an adaptive radar system. The aim is to achieve enhanced feature extraction performance for multiple extended targets. There are two scenarios to consider: multiple extended targets separated in range and multiple extended targets close in range. We propose a waveform optimization scheme based on Kalman filtering by minimizing the mean square error of separated target scattering coefficient estimation and a waveform optimization approach by minimizing the mean square error of closed power spectrum density estimation. A convex cost function is established, and the optimal solution can be obtained using the existing convex programming algorithm. With subsequent iterations of the algorithm, the simulation results demonstrate an improvement in the estimation of target parameters from the dynamic scene, such as target scattering coefficient and power spectrum density, while maintaining relatively lower computational complexity.
Year
DOI
Venue
2019
10.1007/s10957-018-01466-8
Journal of Optimization Theory and Applications
Keywords
Field
DocType
Kalman filtering, Target scattering coefficient estimation, Power spectrum density estimation, Waveform optimization, Multiple extended targets, 15A69, 81P40, 90C3
Density estimation,Mathematical optimization,Waveform,Algorithm,Mean squared error,Kalman filter,Spectral density,Estimation theory,Convex optimization,Mathematics,Computational complexity theory
Journal
Volume
Issue
ISSN
181
2
1573-2878
Citations 
PageRank 
References 
1
0.36
21
Authors
3
Name
Order
Citations
PageRank
Yu Yao110.69
Zhao Junhui213919.70
Lenan Wu370062.18