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Low-Complexity Joint 3D Super-Resolution Estimation of Range Velocity and Angle of Multi-Targets Based on FMCW Radar.
- Source :
-
Sensors (14248220) . Sep2022, Vol. 22 Issue 17, p6474. 19p. - Publication Year :
- 2022
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14248220
- Volume :
- 22
- Issue :
- 17
- Database :
- Academic Search Index
- Journal :
- Sensors (14248220)
- Publication Type :
- Academic Journal
- Accession number :
- 159033528
- Full Text :
- https://doi.org/10.3390/s22176474