Abstract
This paper proposes a high-efficiency super-resolution frequency-modulated continuous-wave (FMCW) radar algorithm based on estimation by fast Fourier transform (FFT). In FMCW radar systems, the maximum number of samples is generally determined by the maximum detectable distance. However, targets are often closer than the maximum detectable distance. In this case, even if the number of samples is reduced, the ranges of targets can be estimated without degrading the performance. Based on this property, the proposed algorithm adaptively selects the number of samples used as input to the super-resolution algorithm depends on the coarsely estimated ranges of targets using the FFT. The proposed algorithm employs the reduced samples by the estimated distance by FFT as input to the super resolution algorithm instead of the maximum number of samples set by the maximum detectable distance. By doing so, the proposed algorithm achieves the similar performance of the conventional multiple signal classification algorithm (MUSIC), which is a representative of the super resolution algorithms while the performance does not degrade. Simulation results demonstrate the feasibility and performance improvement provided by the proposed algorithm; that is, the proposed algorithm achieves average complexity reduction of compared to the conventional MUSIC algorithm while achieving its similar performance. Moreover, the improvement provided by the proposed algorithm was verified in practical conditions, as evidenced by our experimental results.
Highlights
The ultra wide band (UWB) radar systems with highresolution and high-precision had been in the spotlight as a representative radar system [3]
To reduce the computational complexity while exploiting the high-resolution features of super-resolution-based estimators, the algorithm proposed in this paper reduces the Sensors 2021, 21, 4018 number of samples used as input to the multiple signal classification algorithm (MUSIC) algorithm, based on the beat frequency estimated by the fast Fourier transform (FFT)
In this paper, we mathematically show the process of how many reduced samples were required for the same performance according to the ratio of the distance estimated by the FFT and the maximum detection distance
Summary
Radar sensors are a subject of research in various fields, such as defense, space, and vehicles, given their robustness against several conditions, including wind, rain, fog, light, humidity, and temperature [1,2,3,4,5,6]. The ultra wide band (UWB) radar systems with highresolution and high-precision had been in the spotlight as a representative radar system [3]. The UWB radar systems employ very narrow pulse width and they require very wide bandwidth [7,8]. This is the reason for the high complexity of the UWB radar systems
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