Instantaneous grating signal subdivision system with non-linear Kalman filters

Abstract

Grating encoder is a sinusoidal encoder based on grating diffraction principle, which is currently utilized in many high-precision displacement systems because of its advantageous characteristics: low cost, simple structure, works in harsh environments, high reliability, and so on. The output signal of grating encoder usually contains noise interference error, amplitude inconsistency error, DC bias error, harmonic error and quadrature phase error. These non-ideal factors are the main reasons for affecting the precision of subdivision. In the traditional signal subdivision system, it is usually necessary to compensate each kind of error separately, which will consume many hardware and computing resources and cause a significant output latency, especially in the filtering section and normalization section. In this paper, a non-linear Kalman filter-based sin-cos wave subdivision method is proposed. Compared with the traditional filtering methods, non-linear Kalman filter has higher dynamic response and can provide instantaneous phasor estimation. In addition, it can simultaneously achieve filtering, amplitude normalization, decoupling DC bias, harmonic suppression, and phase compensation functions, which significantly reduces the computational burden and facilitates the implementation on low-cost processors. In this study, a non-linear Kalman filter-based signal segmentation system is implemented on an FPGA platform and verified on a six-degree-of-freedom grating ruler platform. The results show that the single-channel output delay is only 1.8us at a 50MHz clock, which has a very high real-time ability. When the frequency and amplitude of the input signal varies, the non-linear Kalman filter can track instantaneously and has high dynamic characteristics. Experimental results show the effectiveness of this method.