To combat the impacts of uncertain noise on estimation vehicle state parameters and high cost sensors, a state-observer design with an adaptive unscented Kalman filter (AUKF) is developed. The equation observer derived by establishing vehicle’s three degrees-of-freedom (DOF) model. On this basis, Sage–Husa algorithm (UKF) are combined to form AUKF adaptively update statistical feature measureme...

In this paper, an improved Precise Point Positioning GPS/MEMS-based integrated system is introduced for precise positioning applications. Un-differenced ionosphere-free linear combinations of carrier phase and code measurements are processed. Tropospheric delay, satellite clock, ocean loading, Earth tide, carrier-phase windup, relativity, and satellite and receiver antenna phase-center variatio...

In this paper, an improved nonlinear Gaussian mixture probability hypothesis density (GM-PHD) filter is proposed to address bearings-only measurements in multi-target tracking. The proposed method, called the Gaussian mixture measurements-probability hypothesis density (GMM-PHD) filter, not only approximates the posterior intensity using a Gaussian mixture, but also models the likelihood functi...

This paper presents an approach to compensate the effects of noise with an Interacting Multiple Model algorithm using Unscented Kalman Filters (IMM-UKF) in log-spectral domain. The performance of this approach is studied experimentally on a continuous digits recognition task with additive noise conditions and compared with results previously obtained by the implementation of the Interacting Mul...

This article proposes a detailed nonlinear mathematical model of an antagonistic pneumatic artificial muscle (PAM) actuator system for estimating the joint angle and torque using unscented Kalman filter (UKF). The proposed is described in hybrid state-space representation. It includes contraction force PAM, dynamics, fluid dynamics compressed air, mass flows valve, friction models. A part model...

This paper is concerned with filtering nonlinear multivariate time series. A new approximate Bayesian algorithm is proposed which generates sample points and corresponding probability weights that match exactly the predicted values of average marginal skewness and average marginal kurtosis of the unobserved state variables, in addition to matching their mean and the covariance matrix. The perfo...

In light of the intuition that a better symmetrical structure can further increase the numerical accuracy, the paper by Fan and Zeng 2009 developed a new sigma point construction strategy for the unscented Kalman filter UKF , namely, geometric simplex sigma points GSSP . This comment presents a different perspective from the standpoint of the numerical integration. In this respect, the GSSP con...

Acoustic travel-time tomography of the atmosphere is a nonlinear inverse problem which attempts to reconstruct temperature and wind velocity fields in the atmospheric surface layer using the dependence of sound speed on temperature and wind velocity fields along the propagation path. This paper presents a statistical-based acoustic travel-time tomography algorithm based on dual state-parameter ...

Some applications are constrained only to implement low cost receivers. In this case, designers are required to use less complex and non-expensive modulation techniques. Differential Quadrature Phase Shift Keying (DQPSK) and Gaussian Frequency Shift Keying (GFSK) can be non-coherently demodulated with simple algorithms. However, these types of demodulation are not robust and suffer from poor pe...