Kalman filter is one of the most effective methods to recover the signal influenced by noise. Kalman filter algorithm is implemented by the MicroBlaze embedded in SoC (System on Chip) system. A software platform for validating the algorithm is proposed and a case study is given to illustrate its application.
Kalman filter is one of the most essential and important computing methods in the fields of control, signal processing and communication. In the past, mostly Kalman filter is implemented by DSP, but the operating speed could not meet the requirement. Therefore, the study will research the implement methods of Kalman filter based on FPGA. MicroBlaze soft core and VHDL (Hardware Description Language) are used to implement Kalman filter. The operating results will be analyzed and compared with each other.
The Federal Kalman filter is a kind of high operational efficiency autoregressive filter, it can estimate the dynamic system status values from measurement data containing noise. This article does some research about how to implement Federal Kalman filter with VHDL language on an FPGA platform. The design successfully loaded into the FPGA platform and operated normally.
Multiple faults detection has great significance in practice. A dynamic reconfiguration SoC (System on Chip) system based on FPGA (Field Programmable Gate Array) is designed to realize multiple faults detection and reduce the detection time. Also, a framework of software platform and a case study for demonstrating and validating the SoC dynamic reconfiguration system are proposed.
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