MIMO High Frequency Surface Wave Radar Using Sparse Frequency FMCW Signals
The heavily congested radio frequency environment severely limits the signal bandwidth of the high frequency surface wave radar (HFSWR). Based on the concept of multiple-input multiple-output (MIMO) radar, we propose a MIMO sparse frequency HFSWR system to synthesize an equivalent large bandwidth wa...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2017/7514916 |
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| author | Mengguan Pan Baixiao Chen |
| author_facet | Mengguan Pan Baixiao Chen |
| author_sort | Mengguan Pan |
| collection | DOAJ |
| description | The heavily congested radio frequency environment severely limits the signal bandwidth of the high frequency surface wave radar (HFSWR). Based on the concept of multiple-input multiple-output (MIMO) radar, we propose a MIMO sparse frequency HFSWR system to synthesize an equivalent large bandwidth waveform in the congested HF band. The utilized spectrum of the proposed system is discontinuous and irregularly distributed between different transmitting sensors. We investigate the sparse frequency modulated continuous wave (FMCW) signal and the corresponding deramping based receiver and signal processor specially. A general processing framework is presented for the proposed system. The crucial step is the range-azimuth processing and the sparsity of the carrier frequency causes the two-dimensional periodogram to fail when applied here. Therefore, we introduce the iterative adaptive approach (IAA) in the range-azimuth imaging. Based on the initial 1D IAA algorithm, we propose a modified 2D IAA which particularly fits the deramping processing based range-azimuth model. The proposed processing framework for MIMO sparse frequency FMCW HFSWR with the modified 2D IAA applied is shown to have a high resolution and be able to provide an accurate and clear range-azimuth image which benefits the following detection process. |
| format | Article |
| id | doaj-art-37beb2fa48154bbd8f14f026d1bc1d97 |
| institution | OA Journals |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-37beb2fa48154bbd8f14f026d1bc1d972025-08-20T02:07:59ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772017-01-01201710.1155/2017/75149167514916MIMO High Frequency Surface Wave Radar Using Sparse Frequency FMCW SignalsMengguan Pan0Baixiao Chen1National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, ChinaNational Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, ChinaThe heavily congested radio frequency environment severely limits the signal bandwidth of the high frequency surface wave radar (HFSWR). Based on the concept of multiple-input multiple-output (MIMO) radar, we propose a MIMO sparse frequency HFSWR system to synthesize an equivalent large bandwidth waveform in the congested HF band. The utilized spectrum of the proposed system is discontinuous and irregularly distributed between different transmitting sensors. We investigate the sparse frequency modulated continuous wave (FMCW) signal and the corresponding deramping based receiver and signal processor specially. A general processing framework is presented for the proposed system. The crucial step is the range-azimuth processing and the sparsity of the carrier frequency causes the two-dimensional periodogram to fail when applied here. Therefore, we introduce the iterative adaptive approach (IAA) in the range-azimuth imaging. Based on the initial 1D IAA algorithm, we propose a modified 2D IAA which particularly fits the deramping processing based range-azimuth model. The proposed processing framework for MIMO sparse frequency FMCW HFSWR with the modified 2D IAA applied is shown to have a high resolution and be able to provide an accurate and clear range-azimuth image which benefits the following detection process.http://dx.doi.org/10.1155/2017/7514916 |
| spellingShingle | Mengguan Pan Baixiao Chen MIMO High Frequency Surface Wave Radar Using Sparse Frequency FMCW Signals International Journal of Antennas and Propagation |
| title | MIMO High Frequency Surface Wave Radar Using Sparse Frequency FMCW Signals |
| title_full | MIMO High Frequency Surface Wave Radar Using Sparse Frequency FMCW Signals |
| title_fullStr | MIMO High Frequency Surface Wave Radar Using Sparse Frequency FMCW Signals |
| title_full_unstemmed | MIMO High Frequency Surface Wave Radar Using Sparse Frequency FMCW Signals |
| title_short | MIMO High Frequency Surface Wave Radar Using Sparse Frequency FMCW Signals |
| title_sort | mimo high frequency surface wave radar using sparse frequency fmcw signals |
| url | http://dx.doi.org/10.1155/2017/7514916 |
| work_keys_str_mv | AT mengguanpan mimohighfrequencysurfacewaveradarusingsparsefrequencyfmcwsignals AT baixiaochen mimohighfrequencysurfacewaveradarusingsparsefrequencyfmcwsignals |