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Yang XIAO Limin LI Jiachao CHANG Kang WU Guang LIANG Jinpei YU
The combination of GPS measurements with the dynamic model via a Kalman filter or an extended Kalman filter, also known as GPS based reduced dynamic orbit determination (RDOD) techniques, have been widely used for accurate and real time navigation of satellites in low earth orbit (LEO). In previous studies, the GPS measurement noise variance is empirically taken as a constant, which is not reasonable because of insufficient prior information or dynamic environment. An improper estimate of the measurement noise may lead to poor performance or even divergence of the filter. In this letter, an adaptive extended Kalman filter (AEKF)-based approach using GPS dual-frequency pseudo-range measurements is presented, where the GPS pseudo-range measurement noise variance is adaptively estimated by the Carrier to Noise Ratio (C/N0) from the tracking loop of GPS receiver. The simulation results show that the proposed AEKF approach can achieve apparent improvements of the position accuracy and almost brings no extra computational burdens for satellite borne processor.
Hiroshi HARADA Takako YAMAMURA Yukiyoshi KAMIO Masayuki FUJISE
An adaptive modulated orthogonal frequency division multiplexing (OFDM) radio transmission scheme that enables efficient data transmission in multipath fading environments is newly proposed. This scheme can be used in standardized multimedia mobile access systems such as ETSI-BRAN, and ARIB-MMAC. It is based on estimating the delay spread and the carrier-to-noise power density ratio (C/N0). The estimation is done using channel estimation symbols that are inserted into the frames of the standard OFDM radio transmission scheme. Computer simulations show that the estimation method results in an average BER close to those when propagation characteristics are perfectly estimated. Furthermore, when the adaptive OFDM transmission scheme is based on BPSK, QPSK or 16 QAM, the average BER is almost close to that when BPSK-OFDM is only used, and the average transmission rate is 1.8 times as high. Using an error-correction code based on convolutional code results in an average BER lower than that with the BPSK- and QPSK-OFDM schemes.