Adaptive Target Separation Detection
This article considers target separation detection (TSD) in the presence of homogeneous Gaussian interference. The problem is formulated as a hypothesis test for two typical situations: 1) the use of a low range-resolution radar or fast-track update rate; 2) the use of a high-resolution radar or low...
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| Veröffentlicht in: | IEEE transactions on aerospace and electronic systems 2021-02, Vol.57 (1), p.293-309 |
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| container_title | IEEE transactions on aerospace and electronic systems |
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| creator | Gao, Yongchan Aubry, Augusto De Maio, Antonio Ji, Hongbing |
| description | This article considers target separation detection (TSD) in the presence of homogeneous Gaussian interference. The problem is formulated as a hypothesis test for two typical situations: 1) the use of a low range-resolution radar or fast-track update rate; 2) the use of a high-resolution radar or low-track update rate. At the design stage, TSD tests are devised according to the generalized likelihood ratio test criterion. The computation of each decision statistic requires the solution of a semidefinite programming problem obtained leveraging the relationship among linear matrix inequalities and nonnegative trigonometric polynomials. All the obtained decision rules ensure the bounded constant false alarm rate property. At the analysis stage, the performance of some benchmark detectors is given in terms of detection and false alarm probabilities. Finally, numerical examples are provided to show the performance of the proposed tests as compared with the benchmarks as well as the gain achievable over some counterparts devised to monitor a separation event. |
| doi_str_mv | 10.1109/TAES.2020.3018898 |
| format | Article |
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The problem is formulated as a hypothesis test for two typical situations: 1) the use of a low range-resolution radar or fast-track update rate; 2) the use of a high-resolution radar or low-track update rate. At the design stage, TSD tests are devised according to the generalized likelihood ratio test criterion. The computation of each decision statistic requires the solution of a semidefinite programming problem obtained leveraging the relationship among linear matrix inequalities and nonnegative trigonometric polynomials. All the obtained decision rules ensure the bounded constant false alarm rate property. At the analysis stage, the performance of some benchmark detectors is given in terms of detection and false alarm probabilities. Finally, numerical examples are provided to show the performance of the proposed tests as compared with the benchmarks as well as the gain achievable over some counterparts devised to monitor a separation event.</description><subject>Adaptive radar detection</subject><subject>Benchmark testing</subject><subject>Benchmarks</subject><subject>bounded constant false alarm rate</subject><subject>Constant false alarm rate</subject><subject>Covariance matrices</subject><subject>Doppler effect</subject><subject>Doppler radar</subject><subject>False alarms</subject><subject>generalized likelihood ratio test</subject><subject>Likelihood ratio</subject><subject>Linear matrix inequalities</subject><subject>Mathematical analysis</subject><subject>Polynomials</subject><subject>Radar tracking</subject><subject>Semidefinite programming</subject><subject>Separation</subject><subject>Target detection</subject><subject>target separation detection</subject><subject>Target tracking</subject><issn>0018-9251</issn><issn>1557-9603</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kFtLwzAUx4MoWKcfQHwp6GtrTk7SJI9jzgsMfFh9Dml7Kh261rQT_PZr6fDpXPhf4MfYLfAUgNvHfLnepoILniIHY6w5YxEopRObcTxnER-_iRUKLtlV3-_GUxqJEXtYVr4bml-Kcx8-aYi31Pngh6bdx080UDlt1-yi9l893Zzmgn08r_PVa7J5f3lbLTdJKSwOiZIloiGvK69QKVmoCiCzVPtKGYFlBqbQVKMA45UgLUxdSF8ZnkEpOVpcsPs5twvtz4H6we3aQ9iPlU5IY7TMtOajCmZVGdq-D1S7LjTfPvw54G6C4SYYboLhTjBGz93saYjoX29hjFSIR76aWLo</recordid><startdate>20210201</startdate><enddate>20210201</enddate><creator>Gao, Yongchan</creator><creator>Aubry, Augusto</creator><creator>De Maio, Antonio</creator><creator>Ji, Hongbing</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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The problem is formulated as a hypothesis test for two typical situations: 1) the use of a low range-resolution radar or fast-track update rate; 2) the use of a high-resolution radar or low-track update rate. At the design stage, TSD tests are devised according to the generalized likelihood ratio test criterion. The computation of each decision statistic requires the solution of a semidefinite programming problem obtained leveraging the relationship among linear matrix inequalities and nonnegative trigonometric polynomials. All the obtained decision rules ensure the bounded constant false alarm rate property. At the analysis stage, the performance of some benchmark detectors is given in terms of detection and false alarm probabilities. 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| source | IEEE Electronic Library (IEL) |
| subjects | Adaptive radar detection Benchmark testing Benchmarks bounded constant false alarm rate Constant false alarm rate Covariance matrices Doppler effect Doppler radar False alarms generalized likelihood ratio test Likelihood ratio Linear matrix inequalities Mathematical analysis Polynomials Radar tracking Semidefinite programming Separation Target detection target separation detection Target tracking |
| title | Adaptive Target Separation Detection |
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