Fault detection and isolation (FDI) logic plays a crucial role in enhancing the safety and reliability, and reducing the operating cost of aircraft propulsion systems. However, it is a challenging problem achieving the FDI task with high reliability. For this purpose, various approaches have been proposed in the literature. In an on-line engine fault diagnoses, two tasks may use Kalman filter t...

For the mobile robot Simultaneous Localization and Mapping (SLAM),a new algorithm is proposed, and named Adaptive Iterated Square-Root Cubature Kalman Filter based SLAM algorithm (AISRCKF-SLAM). The main contribution of the algorithm is that the numerical integration method based on cubature rule is directly used to calculate the SLAM posterior probability density. To improve innovation covaria...

Carrier tracking in GNSS receivers suffers in environments where platform dynamics, received noise and interference are expected simultaneously. Similar is the case of a Locata receiver which operates on the same basic principles as GNSS receivers. A reduction in tracking loop bandwidth may offer noise rejection, but at the same time it makes tracking more vulnerable to oscillator and platform ...

Accurate state of charge (SOC) estimation is of great significance for a lithium-ion battery to ensure its safe operation and to prevent it from over-charging or over-discharging. However, it is difficult to get an accurate value of SOC since it is an inner sate of a battery cell, which cannot be directly measured. This paper presents an Adaptive Cubature Kalman filter (ACKF)-based SOC estimati...

In this paper, a new nonlinear adaptive filter is presented. This filter consists of three main parts. In the first part, the input space is mapped into the high dimensional space, HDS, using the RBF kernel. The second part employs the Kalman filter as a smoother in HDS. The RLS adaptation algorithm is used for weight updating in the third part. The innovation of this work lies in using Kalman ...

In all speech communication settings the quality and intelligibility of speech is of utmost importance for ease and accuracy of information exchange. Kalman filter is an adaptive least square error filter that provides an efficient computational recursive solution for estimating a signal in presence of noises. Beamforming is another possible method of speech enhancement, because, the beamformer...

Classical extended Kalman filter algorithm is often used to obtain dynamic estimation of nodes’ position in wireless localization. However, it is prone to generate error accumulation in the filtering process, and lead to filter divergence, which causes low accuracy. The paper explores a strong tracking extended Kalman filter with algorithm a fading factor, which can adjust the gain K in real ti...

In this paper, channel parameters are estimated and Adaptive Synchronization is done by using Kalman filter. The channel is assumed to be time varying in nature is modelled as a low-Pass tapped delay line filter. The Kalman filter technique is used to estimate the parameters of the channel with more accuracy. The parameters of the channel are time varying in nature. Channel estimation algorithm...

The study is concerned with a single-parameter adaptive comb filter (ACF), a multi-notch filter with periodically located nulls. The filter is suggested to retrieve a waveform modeled by superposition of harmonics, in particular, periodic non-sinusoidal signal. Using trigonometric constraints between the signal fundamental frequency and over tones results in a non-linear estimation problem. In ...