Signal Processing for Multistatic Radar Systems Adaptive Waveform Selection, Optimal Geometries and Pseudolinear Tracking Algorithms
Auteurs : Nguyen Ngoc Hung, Doğançay Kutluyil
Part 1. Adaptive waveform selection
2. Waveform selection for multistatic tracking of a maneuvering Target
3. Waveform selection for multistatic target tracking in clutter
4. Waveform selection for multistatic target tracking with Cartesian estimates
5. Waveform selection for distributedmultistatic target tracking
Part 2. Optimal geometry analysis
6. Optimal geometries for multistatic target localization with one transmitter and multiple receivers
7. Optimal geometries for multistatic target localization by independent bistatic channels
Part 3. Pseudolinear tracking algorithms
8. Batch track estimators formultistatic target motion analysis
9. Closed-form solutions for multistatic target localization with time-difference-of-arrival measurements
Kutluyil Dogançay received the BS degree with honors in electrical and electronic engineering from Bogaziçi University, Istanbul, Turkey, in 1989, the MSc degree in communications and signal processing from Imperial College, The University of London, UK, in 1992, and the PhD degree in telecommunications engineering from The Australian National University, Canberra, ACT, Australia, in 1996. Since November 1999, he has been with the School of Engineering, University of South Australia, where he is a professor and discipline leader of electrical and mechatronic engineering. His research interests span statistical and adaptive signal processing with applications in defence and communication systems. Dr Dogançay received the Best Researcher Award of School of Engineering, University of South Australia, in 2015, and Tall Poppy Science Award of the Australian Institute of Political Science in 2005. He was the Tutorials Chair of the IEEE Statistical Signal Processing Workshop (SSP 2014), and the Signal Processing and Communications Program Chair of the 2007 Information, Decision and Control Conference. He serves on the Editorial Board of Signal Processing and
- Develops waveform selection algorithms in a multistatic radar setting to optimize target tracking performance
- Assesses the optimality of a given target-sensor geometry and designs optimal geometries for target localization using mobile sensors
- Gives an understanding of low-complexity and high-performance pseudolinear estimation algorithms for target localization and tracking in multistatic radar systems
- Contains the MATLAB codes for the examples used in the book
Date de parution : 10-2019
Ouvrage de 188 p.
15x22.8 cm
Thème de Signal Processing for Multistatic Radar Systems :
Mots-clés :
adaptive waveform selection; ambiguity function; angle-of-arrival (AOA); asymptotical efficiency; bias analysis; bias compensation; bistatic radar; closed-form solution; clutter; computational simplicity; Cramer–Rao lower bounds; Cramér–Rao lower bounds; elliptic TOA localization; estimation confidence region; extended Kalman filter; false-alarm; Fisher information matrix; frequency-difference-of-arrival (FDOA); instrumental variables (IV); interacting multiple model; maneuvering target; maximum-likelihood estimation; multistatic radar; optimal geometry; optimal sensor placement; probabilistic data association; pseudolinear estimation; target localization; target motion analysis; target tracking; time-difference-of-arrival (TDOA); time-of-arrival (TOA); trajectory optimization; waveform diversity