An Ultra-Sensitive Online Calibration-Quality Monitoring Metric for MIMO Radar Systems

The usual radar end-of-line (EOL) tests compensate for amplitude and phase imbalances and mutual coupling in multichannel MIMO radar systems. A high-quality calibration is required to provide a good cross-range imaging performance. However, harsh environmental conditions, like temperature and moisture changes, often experienced, e.g., by automotive radars, change the initially estimated system parameters and degrade the calibration and measuring quality over time. This publication proposes two new metrics that enable an easy implementable online estimation of a radar's overall calibration quality based on generated synthetic aperture radar (SAR) images. The approach exploits the effect that the calibration error power in multichannel SAR systems accumulates in a few analytically predictable positions. Utilizing this knowledge leads to a very high sensitivity of the derived metrics. The high performance of the proposed new method is demonstrated by measurements.