FMCW Radar Estimation Algorithm with High Resolution and Low Complexity Based on Reduced Search Area

We propose a frequency-modulated continuous wave (FMCW) radar estimation algorithm with high resolution and low complexity. The fast Fourier transform (FFT)-based algorithms and multiple signal classification (MUSIC) algorithms are used as algorithms for estimating target parameters in the FMCW rada...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Vol. 22; no. 3; p. 1202
Main Authors: Kim, Bong-Seok, Jin, Youngseok, Lee, Jonghun, Kim, Sangdong
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 05.02.2022
MDPI
Subjects:
Algorithms
Antennas
estimation
FMCW radar
Frequency modulation
low complexity
Musical performances
Radar systems
search area
Sensors
Spectrum allocation
super resolution
Surveillance
Velocity
Canada
estimation
low complexity
super resolution
search area
FMCW radar
ISSN:1424-8220, 1424-8220
Online Access:Get full text
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Summary:We propose a frequency-modulated continuous wave (FMCW) radar estimation algorithm with high resolution and low complexity. The fast Fourier transform (FFT)-based algorithms and multiple signal classification (MUSIC) algorithms are used as algorithms for estimating target parameters in the FMCW radar systems. FFT-based and MUSIC algorithms have tradeoff characteristics between resolution performance and complexity. While FFT-based algorithms have the advantage of very low complexity, they have the disadvantage of a low-resolution performance; that is, estimating multiple targets with similar parameters as a single target. On the other hand, subspace-based algorithms have the advantage of a high-resolution performance, but have a problem of very high complexity. In this paper, we propose an algorithm with reduced complexity, while achieving the high-resolution performance of the subspace-based algorithm by utilizing the advantages of the two algorithms; namely, the low-complexity advantage of FFT-based algorithms and the high-resolution performance of the MUSIC algorithms. The proposed algorithm first reduces the amount of data used as input to the subspace-based algorithm by using the estimation results obtained by FFT. Secondly, it significantly reduces the range of search regions considered for pseudo-spectrum calculations in the subspace-based algorithm. The simulation and experiment results show that the proposed algorithm achieves a similar performance compared with the conventional and low complexity MUSIC algorithms, despite its considerably lower complexity.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s22031202