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| Content Provider | Springer Nature Link |
|---|---|
| Author | Zhao, Yi nan Li, Feng cong Zhang, Tao Zhou, Zhi quan |
| Copyright Year | 2014 |
| Abstract | We propose an approach to design waveform sets with good auto- and cross-correlation properties. The designed waveform sets can be used for multiple-input multiple-output radars to minimize the cross-interference, and consequently improve the radar performance. Firstly, we transform the original correlation optimization problem into a spectral approximation problem. Secondly, we define the objective function based on the square error between the designed waveform matrix and the ideal one. Finally, the problem is solved by using an algorithm based on alternating projection and phase retrieval. We further improve the proposed method, and derive an extended version to design waveforms with sparse spectrum and good correlation property for combating electronic jamming. The algorithms are computationally efficient because their main steps are based on fast Fourier transform. The effectiveness of the proposed approach is demonstrated by numerical simulations. |
| Starting Page | 43 |
| Ending Page | 60 |
| Page Count | 18 |
| File Format | |
| ISSN | 09236082 |
| Journal | Multidimensional Systems and Signal Processing |
| Volume Number | 27 |
| Issue Number | 1 |
| e-ISSN | 15730824 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2014-06-10 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | MIMO radar Waveform design Alternating projection Autocorrelation Cross-correlation Sparse spectrum Circuits and Systems Electrical Engineering Signal, Image and Speech Processing Artificial Intelligence (incl. Robotics) |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Artificial Intelligence Signal Processing Information Systems Computer Science Applications Software Hardware and Architecture |
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