In order to meet the urgent requirement for accurate retrieval of liquid cloud microphysical properties, integrating the detecting advantages of active and passive sensors and combining radar reflectivity and optical depth information from CloudSat and Aqua, a new retrieval algorithm of liquid cloud microphysical parameters is proposed according to the optimal estimation theory. By assuming the lognormal size distribution of cloud droplets and establishing functional relationships between measurement and retrieval variables based on forward physical model, with the prior information about spectral distribution parameters, the optimal solutions of spectral parameters are obtained after iteratively calculating, then the microphysical parameters of liquid cloud could be retrieved based on forward physical model, and the uncertainty can be calculated according to error propagation theory. By designing retrieval scheme and using measured case data, the retrieval results are compared with the data published by CloudSat official institutions and those retrieved using empirical algorithms, showing that retrievals of liqiud cloud microphysical parameters based on optimal estimation theory by using combined active and passive sensor data are well consistent with official released data, which makes up for the disadvantages of empirical algorithms that have large error and poor expansibility and gives some important references for retrieval research of liquid cloud microphysical parameters based on domestic spaceborne and airborne W-band millimeter-wave radar data.

This paper designs and implements a High Speed Redundant IO Bus for Energy Power Controller System. The physical layer adopts multi-point low-voltage differential signal standard. This bus has the characteristics of high real-time, high throughput and easy expansion. The controller communicates with IO module by A/B bus alternately, monitors link status in real time and collects IO module data. Non real time slots can be used to control non real time messages for IO modules such as time synchronizing and memory monitoring. The controller ARM core runs QNX real-time operating system, and transmits the message needed to communicate with IO modules to the FPGA through DMA. After receiving the message, the FPGA parses the message and automatically fills in the CRC check code and frame end flag at the end of the message. When the FPGA receives the data feedback from the IO module, it performs CRC verification. If the verification passes, it fills the corresponding module receiving buffer. Otherwise, it fills the CRC verification error flag in the register of the corresponding IO module to reduce the load of the arm core.