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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hai Deng Himed, B. |
| Copyright Year | 2009 |
| Description | Author affiliation: Air Force Research Labs, Wright-Patterson AFB, Ohio 45433, USA (Himed, B.) || University of North Texas, Denton, 76203, USA (Hai Deng) |
| Abstract | For airborne radar systems, space-time adaptive processing (STAP) is the approach that is normally adopted to detect ground moving targets in ground clutter, but the technique becomes less effective if the speed of ground moving targets is very low because of the proximity of the Doppler frequency of targets to that of ground clutter. Typical low-speed ground target detection scenarios include detecting ground troops and slowly-moving ground vehicles. Multiple-Input Multiple-Output (MIMO) radar possesses multiple transmitting and receiving channels providing additional diversified reflections for fusion processing in target detection and measurements. MIMO radar has been extensively investigated [1, 2]; but the exact structure of MIMO radar is defined widely different. In this work, an innovative multi-level MIMO radar signal processing architecture is proposed for airborne systems to effectively detect low-speed ground moving targets. The new MIMO-based approach is demonstrated to be effective for detecting such low-speed ground targets in this work, and some simulation results are presented subsequently. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 1214108 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424436477 |
| ISSN | 15223965 |
| DOI | 10.1109/APS.2009.5172132 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-06-01 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Radar detection MIMO Doppler radar Clutter Object detection Airborne radar Adaptive systems Frequency Vehicle detection Land vehicles |
| Content Type | Text |
| Resource Type | Article |
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