This paper is concerned with the filtering problem caused by the inaccuracy variance of measurement noise in real nonlinear systems. A novel weighted fusion estimation method of multiple different variance estimators is presented to estimate the vari...
The demands for indoor positioning in location-based services (LBS) and applications grow rapidly. It is beneficial for indoor positioning to combine attitude and heading information. Accurate attitude and heading estimation based on magnetic, angula...
Initial alignment is critical and indispensable for the inertial navigation system (INS), which determines the initial attitude matrix between the reference navigation frame and the body frame. The conventional initial alignment methods based on the...
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...
The features of measurement and process noise are directly related to the optimal performance of the cubature Kalman filter. The maneuvering target model’s high level of uncertainty and non-Gaussian mean noise are typical issues that the radar...
In the navigation of an autonomous underwater vehicle (AUV), the positioning accuracy and stability of the navigation system will decrease due to uncertainties such as mobility, inaccuracy of a priori process noise characteristic, and simplification...
The state of charge (SOC) of a lithium-ion battery plays a key role in ensuring the charge and discharge energy control strategy, and SOC estimation is the core part of the battery management system for safe and efficient driving of electric vehicles...
The maximum correntropy criterion (MCC), as an effective method for dealing with anomalous measurement noise, is widely applied in the design of filters. However, its performance largely depends on the proper setting of the kernel bandwidth, and curr...
An accurate state of charge (SOC) estimation of the on-board lithium-ion battery is of paramount importance for the efficient and reliable operation of electric vehicles (EVs). Aiming to improve the accuracy and reliability of battery SOC estimation,...
In this paper, we propose a robust adaptive cubature Kalman filter (CKF) to deal with the problem of an inaccurately known system model and noise statistics. In order to overcome the kinematic model error, we introduce an adaptive factor to adjust th...
Accurate online parameter identification and state of charge (SOC) estimation are both very crucial for ensuring the operating safety of lithium-ion batteries and usually the former is a base of the latter. To achieve accurate and stable SOC estimati...
Inertial navigation systems experience error accumulation over time, leading to the use of integrated navigation as a classical solution to mitigate inertial drift. This provides a novel approach to navigation and positioning by using the combined ad...
This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation syste...
Small unmanned aerial vehicles are now commonly equipped with integrated navigation systems to obtain high-precision navigation parameters. However, affected by the dual impacts of multipath effects and dynamic environmental changes, their state esti...
Aiming at the problems of Non-Line-of-Sight (NLOS) observation errors and inaccurate kinematic model in ultra-wideband (UWB) systems, this paper proposed an improved robust adaptive cubature Kalman filter (IRACKF). Robust and adaptive filtering can w...
With the development of location-based service (LBS), indoor positioning based on pedestrian dead reckoning (PDR) has become a hot research topic. Smartphones are becoming more popular for indoor positioning. This paper proposes a two-step robust-ada...
In complex urban environments, a single Global Navigation Satellite System (GNSS) is often not ideal for navigation due to a lack of sufficient visible satellites. Additionally, the heading angle error of a GNSS/micro-electro-mechanical system–grade...
Compared with a scalar tracking receiver, the Beidou vector tracking receiver has the advantages of smaller tracking errors, fast loss-of-lock reacquisition, and high stability. However, in extremely challenging conditions, such as highly dynamic and...
Simultaneous state and parameter estimation is essential for control system design and dynamic modeling of physical systems. This capability provides critical real-time insight into system behavior, supports the discovery of underlying mechanisms, an...
With the widespread application of information technology in microgrids, microgrids are evolving into a class of power cyber–physical systems (CPSs) that are deeply integrated with physical and information systems. Due to the high dependence of...
For the degradation of the filtering performance of the INS/CNS navigation system under measurement noise uncertainty, an adaptive cubature Kalman filter (CKF) is proposed based on improved empirical mode decomposition (EMD) and a resampling-free sig...
Under large azimuth misalignment conditions, the initial alignment of strapdown inertial navigation systems (SINS) is challenged by the nonlinear characteristics of the error model. Traditional particle filter (PF) algorithms suffer from the inapprop...
An accurate state of charge (SOC) estimation is vital for safe operation and efficient management of lithium-ion batteries. To improve the accuracy and robustness, an adaptive and robust square root cubature Kalman filter based on variational Bayesia...
Accurate state-of-charge (SOC) estimation of lithium batteries is of great significance for electric vehicles. In this paper, a combined estimation method of multi-innovation unscented Kalman filter (MIUKF) and fractional order square root cubature K...
For a land-vehicle strapdown inertial navigation system (SINS), the problem of initial alignment with large misalignment angle in-motion needs to be solved urgently. This paper proposes an improved ACKF/KF initial alignment method for SINS aided by o...
Aimed at solving the problem of decreased filtering precision while maneuvering target tracking caused by non-Gaussian distribution and sensor faults, we developed an efficient interacting multiple model-unscented Kalman filter (IMM-UKF) algorithm. B...
Indoor localization based on pedestrian dead reckoning (PDR) is drawing more and more attention of researchers in location-based services (LBS). The demand for indoor localization has grown rapidly using a smartphone. This paper proposes a 3D indoor...
Road roughness significantly impacts vehicle safety and dynamic responses. For nonlinear suspension systems, the nonlinear characteristics often make it challenging for estimators to identify the actual road roughness accurately. This paper proposes...
In this paper, a co-estimation scheme of the state of charge (SOC) and available capacity is proposed for lithium–ion batteries based on the adaptive model-based algorithm. A three-dimensional response surface (TDRS) in terms of the open circui...
Hypersonic targets have complex motion states and high maneuverability. The traditional interactive multi-model (IMM) has low tracking accuracy and a slow convergence speed. Therefore, this paper proposes a strong tracking cubature Kalman filter (CKF...
The active aircraft defense problem is investigated for the stochastic scenario wherein a defending missile (or a defender) is employed to protect a target aircraft from an attacking missile whose pursuit guidance strategy is unknown. For the purpose...
In this article, a fast krill herd algorithm is developed for prognosis of hybrid mechatronic system using the improved Wiener degradation process. First, the diagnostic hybrid bond graph is used to model the hybrid mechatronic system and derive glob...
A variety of accurate information inputs are of great importance for automotive control. In this paper, a novel joint soft-sensing strategy is proposed to obtain multi-information under diverse vehicle driving scenarios. This strategy is realized by...
In order to defend the hypersonic glide vehicle (HGV), a cost-effective single-model tracking algorithm using Cubature Kalman filter (CKF) is proposed in this paper based on modified aerodynamic model (MAM) as process equation and radar measurement m...
The mapping between open circuit voltage (OCV) and state of charge (SOC) is critical to the lithium-ion battery management system (BMS) for electric vehicles. In order to solve the poor accuracy in the local SOC range of most OCV models, an OCV model...
An adaptive constant acceleration (ACA) model is proposed for the maneuvering target tracking problem. Based on the Taylor series expansion of acceleration, we establish the relationship between the Jerk and the velocity as well as the acceleration s...
As an optimal estimation method, the Kalman filter is the most frequently-used data fusion strategy in the field of dynamic navigation and positioning. Nevertheless, the abnormal model errors seriously degrade performance of the conventional Kalman f...
In this paper, an improved cubature Kalman filtering (CKF) is proposed using the Sigmoid function to address the problems of positioning accuracy degradation and large deviations in ultra-wideband (UWB) indoor positioning in non-line-of-sight environ...
Accurate and reliable estimation information of sideslip angle is very important for intelligent motion control and active safety control of an autonomous vehicle. To solve the problem of sideslip angle estimation of an autonomous vehicle, a sideslip...
The model of bearings-only tracking is generally described by discrete–discrete filtering systems. Discrete robust methods are also frequently used to address measurement uncertainty problems in bearings-only tracking. The recently popular cont...
Nonlinear filtering algorithms have significant implications in the optimal estimation of navigation states and in improving the accuracy, reliability, and robustness of navigation systems. This manuscript surveys the developments of the nonlinear fi...
For manoeuvring surface target tracking in the presence of glint noise, Huber-based Kalman filters have been widely regarded as effective. However, when the proportion of outlier measurements is high, their numerical stability and estimation accuracy...
With regard to the rear-drive in-wheel motor vehicle, this paper studies the joint estimation method for the vehicle state and road adhesion coefficient. A nonlinear seven degrees of freedom vehicle estimation model and a tire estimation model are es...
Standard Bayesian filtering algorithms only work well when the statistical properties of system noises are exactly known. However, this assumption is not always plausible in real target tracking applications. In this paper, we present a new estimatio...
Energy-optimal adaptive cruise control (EACC) is becoming increasingly popular due to its ability to save energy. Considering the negative impacts of system noise on the EACC, an improved modified model predictive control (MPC) is proposed, which com...
In this article, a multisensor joint localization system is proposed based on modified cubature Kalman filtering, which aims to improve the accuracy of state estimation under a moderate computational burden in the presence of high process noise. Spec...
Bearings-only tracking only adopts measurements from angle sensors to realize target tracking, thus, the accuracy of the state prediction has a significant influence on the final results of filtering. There exist unpredictable approximation errors in...
Multi-source nonlinear noise exists in the process of multi-source navigation information fusion in long-endurance positioning systems in complex environments. In such engineering applications, the classical Kalman filter (KF) and the extended Kalman...
State estimation is widely used in various automated systems, including IoT systems, unmanned systems, robots, etc. In traditional state estimation, measurement data are instantaneous and processed in real time. With modern systems’ development, sens...
This paper investigates the numerical integration error calibration problem in Lie group sigma point filters to obtain more accurate estimation results. On the basis of the theoretical framework of the Bayes–Sard quadrature transformation, we f...
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