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Low-Complexity Joint 3D Super-Resolution Estimation of Range Velocity and Angle of Multi-Targets Based on FMCW Radar
| Content Provider | MDPI |
|---|---|
| Author | Li, Yingchun Long, Qi Wu, Zhongjie Zhou, Zhiquan |
| Copyright Year | 2022 |
| Description | Multi-dimensional parameters joint estimation of multi-targets is introduced to implement super-resolution sensing in range, velocity, azimuth angle, and elevation angle for frequency-modulated continuous waveform (FMCW) radar systems. In this paper, a low complexity joint 3D super-resolution estimation of range, velocity, and angle of multi-targets is proposed for an FMCW radar with a uniform linear array. The proposed method firstly constructs the size-reduced 3D matrix in the frequency domain for the system model of an FMCW radar system. Secondly, the size-reduced 3D matrix is established, and low complexity three-level cascaded 1D spectrum estimation implemented by applying the Lagrange multiplier method is developed. Finally, the low complexity joint 3D super-resolution algorithms are validated by numerical experiments and with a 77 GHz FMCW radar built by Texas Instruments, with the proposed algorithm achieving significant estimation performance compared to conventional algorithms. |
| Starting Page | 6474 |
| e-ISSN | 14248220 |
| DOI | 10.3390/s22176474 |
| Journal | Sensors |
| Issue Number | 17 |
| Volume Number | 22 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2022-08-28 |
| Access Restriction | Open |
| Subject Keyword | Sensors Imaging Science Fmcw Radar Super Resolution Array Signal Processing |
| Content Type | Text |
| Resource Type | Article |
