Hybrid signal processing techniques for shared spectrum multistatic radars
View/ Open
Issue Date
2007-05-31Author
Dower, William
Publisher
University of Kansas
Type
Thesis
Degree Level
M.S.
Discipline
Electrical Engineering & Computer Science
Rights
This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author.
Metadata
Show full item recordAbstract
Multiple radars transmitting a waveform at the same time on the same band will cause interference that most pulse compression algorithms cannot suppress effectively. The Multistatic Adaptive Pulse Compression (MAPC) algorithm and other adaptive algorithms have demonstrated the ability to suppress interference from other radars transmitting on the same band and the sidelobes that form due to the waveform that the radar of interest transmits. Another algorithm that has been used to mitigate the effects of sidelobes using pulse compression is the CLEAN algorithm which has been used by radio astronomers since the 1970's as a way to deconvolve a received signal.To improve the performance of the MAPC algorithm, two variants of the CLEAN algorithm were developed to eliminate scatterers with a large SNR that are causing interference within the received radar signal so that the MAPC algorithm is able to further suppress interference from other radars. Also two different methods for integrating the newly developed CLEAN algorithms with the MAPC algorithm have been developed and tested in this thesis to create a hybrid algorithm. Compared to the MAPC algorithm the one of the hybrid algorithms is able to detect a scatterer that has 10 dB less signal to noise ratio (SNR) at a probability of detection of 0.9. By combining the MAPC and CLEAN algorithms the probability of detecting scatterers with a small signal to noise ratio improves along with the mean squared error of the range profile.
Description
Thesis (M.S.)--University of Kansas, Electrical Engineering & Computer Science, 2007.
Collections
- Theses [4036]
Items in KU ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
We want to hear from you! Please share your stories about how Open Access to this item benefits YOU.