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.

In this letter, a novel on-orbit estimation and calibration method of GPS antenna geometry offsets for attitude determination of LEO satellites is proposed. Both baseline vectors in the NED coordinate system are achieved epoch-by-epoch firstly. Then multiple epochs' baseline vectors are united to compute all the offsets via an UKF for a certain long time. After on-orbit estimation and calibration, instantaneous and accurate attitude can be achieved. Numerical results show that the proposed method can obtain the offsets of each baseline in all directions with high accuracy estimation and small STDs, and effective attitudes can be achieved after antenna geometry calibration using the estimated offsets. The high accuracy give the proposed scheme a strong practical-oriented ability.

Movement of the thighs is an important factor for studying gait cycle. In this paper, a hybrid hidden Markov model (HMM)/Kalman filter (KF) scheme is proposed to track the hip angle during gait cycles. Within such a framework, HMM and KF work in parallel to estimate the hip angle and detect major gait events. This approach has been applied to study gait features of different subjects and compared with video based approach. Experimental results indicate that 1.) the swing angle of the hip can be detected with simple hardware configuration using biaxial accelerometers and 2.) the hip angle can be tracked for different subjects within the error range of -5°+5°.

In this letter, a new rapid and accurate synchronization scheme based on PMF-FFT for high dynamic GPS receiver is proposed, with a fine Doppler frequency estimation inserted between the acquisition and tracking modules. Fine Doppler estimation is firstly achieved through a simple interpolation of the PMF-FFT outputs in terms of LSE criterion. Then a high dynamic tracking loop based on UKF is designed to verify the synchronization speed and accuracy. Numerical results show that the fine frequency estimation can closely approach the CRB, and the high dynamic receiver can obtain fine synchronization rapidly just through a very narrow bandwidth. The simplicity and low complexity give the proposed scheme a strong and practical-oriented ability, even for weak GPS signals.

In this letter, a new and accurate frequency estimation method of complex exponential signals is proposed. The proposed method divides the signal samples into several identical segments and sums up the samples belonging to the same segment respectively. Then it utilizes fast Fourier transform (FFT) algorithm with zero-padding to obtain a coarse estimation, and exploits three Fourier coefficients to interpolate a fine estimation based on least square error (LSE) criterion. Numerical results show that the proposed method can closely approach the Cramer-Rao bound (CRB) at low signal-to-noise ratios (SNRs) with different estimation ranges. Furthermore, the computational complexity of the proposed method is proportional to the estimation range, showing its practical-oriented ability. The proposed method can be useful in several applications involving carrier frequency offset (CFO) estimation for burst-mode satellite communications.

In this letter, we investigate the problem of feedforward timing estimation for burst-mode satellite communications. By analyzing the correlation property of frame header (FH) acquisition in the presence of sampling offset, a novel data-aided feedforward timing estimator that utilizes the correlation peaks for interpolating the fractional timing offset is proposed. Numerical results show that even under low signal-to-noise ratio (SNR) and small rolloff factor conditions, the proposed estimator can approach the modified Cramer-Rao bound (MCRB) closely. Furthermore, this estimator only requires two samples per symbol and can be implemented with low complexity with respect to conventional data-aided estimators.