A Novel Nonlinearity Correction Algorithm for FMCW Radar Systems for Optimal Range Accuracy and Improved Multitarget Detection Capability

• Published in: Electronics (Basel) Vol. 8; no. 11; p. 1290
• Main Authors: Toker, Onur, Brinkmann, Marius
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2019
• Subjects: Algorithms; Calibration; Continuous radiation; Decomposition; Design optimization; Design techniques; FIR filters; Hardware; Interpolation; Noise; Nonlinearity; Radar equipment; Radar imaging; Radar systems; Signal processing; Simulation; Synthetic aperture radar; Voltage controlled oscillators
• ISSN: 2079-9292; 2079-9292
• DOI: 10.3390/electronics8111290

Frequency-modulated continuous wave (FMCW) radars are an important class of radar systems, and they are quite popular because of their simpler architecture and lower cost. A fundamental problem in FMCW radars is the nonlinearity of the voltage-controlled oscillator (VCO), which results in a range of measurement errors, problems in multitarget detection, and degradation in synthetic aperture radar (SAR) images. In this paper, we first introduce a novel upsampling theory, then propose new algorithms to improve range accuracy and multitarget detection capability. These improvements are demonstrated both by simulations and actual lab experiments on a 2.4 GHz radar system. There are several techniques reported in the literature for VCO nonlinearity correction, but what makes the proposed approach different is that we focus on real-time processing on low-cost hardware and optimize the design subject to this constraint. We first developed an optimal upsampling theory which is based on almost-causal finite impulse response (FIR) filters. Compared to the sinc-based noncausal interpolation-based upsamplers, the proposed approach is based on using interpolation filters with few number of coefficients. Furthermore, interpolators are trained for a specific class of signals rather than a highly general signal set. Therefore, the proposed approach can be implemented on lower-cost hardware and perform quite well compared to more expensive systems.