Parameter estimation for sparse targets in phased-MIMO radar
Parameter estimation using phased-multiple-input multiple-output (MIMO) radar is investigated in this study, where transmitting antennas are partitioned into subarrays to provide both waveform diversity and high coherent processing gain. By exploiting the target sparsity in the spatial domain, a com...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-06-01
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| Series: | The Journal of Engineering |
| Subjects: | |
| Online Access: | https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0172 |
| _version_ | 1818560317725081600 |
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| author | Can Zhu Ning Zhang Zhimin Chen Peng Chen |
| author_facet | Can Zhu Ning Zhang Zhimin Chen Peng Chen |
| author_sort | Can Zhu |
| collection | DOAJ |
| description | Parameter estimation using phased-multiple-input multiple-output (MIMO) radar is investigated in this study, where transmitting antennas are partitioned into subarrays to provide both waveform diversity and high coherent processing gain. By exploiting the target sparsity in the spatial domain, a compressed sensing-based estimation method is proposed to jointly estimate the direction of arrivals and scattering coefficients of multiple targets in phased-MIMO radar. Cramér-Rao lower bound is derived from setting a performance limit on the presented algorithm, and simulation results are provided to validate its efficiency. Numerical examples reveal that efficient estimation can be obtained when the received signal-to-noise ratio exceeds a threshold at the level of about 5 dB. Also, the authors also show that the number of subarrays and the size of each subarray constitute a fundamental trade-off in improving the estimation performance. |
| first_indexed | 2024-12-14T00:36:57Z |
| format | Article |
| id | doaj.art-7b190d1b9cae40aeb6042eabd4cff964 |
| institution | Directory Open Access Journal |
| issn | 2051-3305 |
| language | English |
| last_indexed | 2024-12-14T00:36:57Z |
| publishDate | 2019-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Journal of Engineering |
| spelling | doaj.art-7b190d1b9cae40aeb6042eabd4cff9642022-12-21T23:24:35ZengWileyThe Journal of Engineering2051-33052019-06-0110.1049/joe.2019.0172JOE.2019.0172Parameter estimation for sparse targets in phased-MIMO radarCan Zhu0Ning Zhang1Zhimin Chen2Peng Chen3Nanjing Marine Radar InstituteNanjing Marine Radar InstituteShanghai Dianji UniversitySoutheast UniversityParameter estimation using phased-multiple-input multiple-output (MIMO) radar is investigated in this study, where transmitting antennas are partitioned into subarrays to provide both waveform diversity and high coherent processing gain. By exploiting the target sparsity in the spatial domain, a compressed sensing-based estimation method is proposed to jointly estimate the direction of arrivals and scattering coefficients of multiple targets in phased-MIMO radar. Cramér-Rao lower bound is derived from setting a performance limit on the presented algorithm, and simulation results are provided to validate its efficiency. Numerical examples reveal that efficient estimation can be obtained when the received signal-to-noise ratio exceeds a threshold at the level of about 5 dB. Also, the authors also show that the number of subarrays and the size of each subarray constitute a fundamental trade-off in improving the estimation performance.https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0172antenna arraysphased array radarcompressed sensingarray signal processingMIMO radartransmitting antennasparameter estimationMIMO communicationradar signal processingestimation performanceparameter estimationsparse targetsphased-MIMO radarphased-multiple-input multiple-output radartransmitting antennassubarraywaveform diversityhigh coherent processing gaintarget sparsitycompressed sensing-based estimation methodmultiple targetsefficient estimationnoise figure 5.0 dB |
| spellingShingle | Can Zhu Ning Zhang Zhimin Chen Peng Chen Parameter estimation for sparse targets in phased-MIMO radar The Journal of Engineering antenna arrays phased array radar compressed sensing array signal processing MIMO radar transmitting antennas parameter estimation MIMO communication radar signal processing estimation performance parameter estimation sparse targets phased-MIMO radar phased-multiple-input multiple-output radar transmitting antennas subarray waveform diversity high coherent processing gain target sparsity compressed sensing-based estimation method multiple targets efficient estimation noise figure 5.0 dB |
| title | Parameter estimation for sparse targets in phased-MIMO radar |
| title_full | Parameter estimation for sparse targets in phased-MIMO radar |
| title_fullStr | Parameter estimation for sparse targets in phased-MIMO radar |
| title_full_unstemmed | Parameter estimation for sparse targets in phased-MIMO radar |
| title_short | Parameter estimation for sparse targets in phased-MIMO radar |
| title_sort | parameter estimation for sparse targets in phased mimo radar |
| topic | antenna arrays phased array radar compressed sensing array signal processing MIMO radar transmitting antennas parameter estimation MIMO communication radar signal processing estimation performance parameter estimation sparse targets phased-MIMO radar phased-multiple-input multiple-output radar transmitting antennas subarray waveform diversity high coherent processing gain target sparsity compressed sensing-based estimation method multiple targets efficient estimation noise figure 5.0 dB |
| url | https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0172 |
| work_keys_str_mv | AT canzhu parameterestimationforsparsetargetsinphasedmimoradar AT ningzhang parameterestimationforsparsetargetsinphasedmimoradar AT zhiminchen parameterestimationforsparsetargetsinphasedmimoradar AT pengchen parameterestimationforsparsetargetsinphasedmimoradar |