A data fusion technique for continuous wave radar sensor using Kalman filter

A novel high precision displacement sensor was developed using phase-based continuous wave radar. This new sensor promises non-contact, high accuracy, high bandwidth, and capability of operating in harsh environments. In this type of radar, minimum two channels are required to uniquely determine phase, which linearly corresponds to displacement. However, extra channels can be used to reduce measurement noise and thus increase the sensor repeatability if used properly. This paper introduces the benefit of a multi-channel over a traditional two-channel system by providing an optimal method to combine data. A Kalman filter is used as a means of data fusion providing an optimal estimation of phase with improved signal quality. Experimental results are provided to verify the validity and effectiveness of the multi-channel algorithm compared with the two-channel.