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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jian Li Guerci, J.R. Luzhou Xu |
| Copyright Year | 1994 |
| Abstract | We consider Signal Waveform's Optimal-under-Restriction Design (SWORD) for active sensing. In the presence of colored interference and noise with known statistical properties, waveform optimization for active sensors such as radar can significantly increase the signal-to-interference-plus-noise ratio needed for much improved target detection. However, the so-obtained optimal waveforms can result in significant modulus variation, poor range resolution, and/or high peak sidelobe levels. To mitigate these problems, we can constrain the waveform optimization problem by restricting the sought-after waveform to be similar to a desired waveform, which is known to have, for example, constant modulus as well as reasonable range resolution and peak sidelobe level. One example of the desired waveform is the widely used linear frequency modulated waveform or chirp. We will provide a detailed solution to the constrained optimization problem and explain how it is related with the existing waveform optimization methods |
| Sponsorship | IEEE Signal Processing Society |
| Starting Page | 565 |
| Ending Page | 568 |
| Page Count | 4 |
| File Size | 254589 |
| File Format | |
| ISSN | 10709908 |
| Volume Number | 13 |
| Issue Number | 9 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-09-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Signal design Constraint optimization Chirp modulation Interference Active noise reduction Colored noise Signal to noise ratio Radar Object detection Signal resolution waveform design Optimization signal-to-noise-plus-interference ratio (SINR) similarity constraint |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Signal Processing Electrical and Electronic Engineering |
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