Results 51 to 60 of about 2,111 (181)
Robust Maximum Correntropy Kalman Filter
ABSTRACTThe Kalman filter provides an optimal estimation for a linear system with Gaussian noise. However, when the noises are non‐Gaussian in nature, its performance deteriorates rapidly. For non‐Gaussian noises, maximum correntropy Kalman filter (MCKF) is developed which provides a more accurate result.
Joydeb Saha, Shovan Bhaumik
openaire +2 more sources
An Adaptive Channel Estimation Based on Fixed-Point Generalized Maximum Correntropy Criterion
Many conventional adaptive channel estimation methods are based on minimum mean square error (MMSE) criterion, maximum correntropy criterion (MCC) or least p-norm criterion.
Pengcheng Yue +3 more
doaj +1 more source
A Novel UWB Positioning Method Based on a Maximum-Correntropy Unscented Kalman Filter
Aiming at the problem of measurement-information abnormal-error and nonlinear filtering in UWB navigation and positioning, an ultra wideband position algorithm based on a maximum cross-correlation entropy unscented Kalman filter is proposed.
Mujie Zhao, Tao Zhang, Di Wang
doaj +1 more source
The complex correntropy is a recently defined similarity measure that extends the advantages of conventional correntropy to complex-valued data. As in the real-valued case, the maximum complex correntropy criterion (MCCC) employs a free parameter called ...
Manoel B. L. Aquino +4 more
doaj +1 more source
This paper addresses channel estimation in mmWave (millimetre wave) hybrid MIMO (multiple‐input multiple‐output) systems impaired by residual transceiver hardware nonidealities, modelled as additive non‐Gaussian noise via Bussgang decomposition. A hyperparameter‐free maximum Versoria criterion (MVC)‐based channel estimator is proposed, featuring a ...
Rangeet Mitra +5 more
wiley +1 more source
A novel robust proportionate affine projection (AP) algorithm is devised for estimating sparse channels, which often occur in network echo and wireless communication channels.
Zhengxiong Jiang +2 more
doaj +1 more source
This paper introduces a Cooperative Adaptive Kalman Filter (CAKF) to prevent filter divergence in a Terrain‐Aided Navigation system by synergistically adapting its process noise (Q), measurement noise (R), and state covariance (P) based on vehicle manoeuvres and terrain quality.
Liyue Liang +5 more
wiley +1 more source
An Examination of Some Signi cant Approaches to Statistical Deconvolution
We examine statistical approaches to two significant areas of deconvolution - Blind Deconvolution (BD) and Robust Deconvolution (RD) for stochastic stationary signals.
Yang, Zi Hua, Yang, Zi Hua
core +1 more source
The burst‐like and high‐amplitude characteristics of impulsive noise, which markedly differ from those of Gaussian noise, render methods based on the Gaussian assumption unable to accurately characterize signals under impulsive noise. Moreover, when dealing with multicomponent signal, existing impulsive noise suppression methods inevitably introduce ...
Weiwei Shang +3 more
wiley +1 more source
This paper concerns the nonlinear filter designing methods in the information space of the nonlinear systems with non-Gaussian noises. Firstly, the prediction information vector is obtained by the traditional square root cubature information filtering ...
Xiaoliang Feng +4 more
doaj +1 more source

