Adaptive Consensus-Based Unscented Information Filter for Tracking Target with Maneuver and Colored Noise

Li, Zhao; Wang, Yidi; Zheng, Wei

doi:10.3390/s19143069

Cited by 12 publications

(5 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Defining the target state as , where and are the position and velocity of the target. The measurement of the ith satellite is , where and are azimuth and elevation, respectively [22]. and are the true and estimated values of the target state at time step k, and .…”

Section: Refined Selection Based On Rapid Observability Analysismentioning

confidence: 99%

Accurately Tracking Hypersonic Gliding Vehicles via an LEO Mega-Constellation in Relay Tracking Mode

Li,

Wang,

Zheng

2024

J. of Syst. Eng. Electron.

View full text Add to dashboard Cite

In order to effectively defend against the threats of the hypersonic gliding vehicles (HGVs), HGVs should be tracked as early as possible, which is beyond the capability of the ground-based radars. Being benefited by the developing megaconstellations in low-Earth orbit, this paper proposes a relay tracking mode to track HGVs to overcome the above problem. The whole tracking mission is composed of several tracking intervals with the same duration. Within each tracking interval, several appropriate satellites are dispatched to track the HGV. Satellites that are planned to take part in the tracking mission are selected by a new derived observability criterion. The tracking performances of the proposed tracking mode and the other two traditional tracking modes, including the stare and track-rate modes, are compared by simulation. The results show that the relay tracking mode can track the whole trajectory of a HGV, while the stare mode can only provide a very short tracking arc. Moreover, the relay tracking mode achieve higher tracking accuracy with fewer attitude controls than the track-rate mode.

show abstract

Section: Refined Selection Based On Rapid Observability Analysismentioning

confidence: 99%

Accurately Tracking Hypersonic Gliding Vehicles via an LEO Mega-Constellation in Relay Tracking Mode

Li,

Wang,

Zheng

2024

J. of Syst. Eng. Electron.

View full text Add to dashboard Cite

show abstract

“…These types of systems are common in practice. For example, in many radar systems, the auto-correlations of measurement noises can not be ignored [29,30] due to the high measurement frequency. In satellite navigation systems, multi-path error and weak GPS signals make the measurement noise regarded as integral to white noise [31].…”

Section: Introductionmentioning

confidence: 99%

Bayesian Cramér-Rao Lower Bounds for Prediction and Smoothing of Nonlinear TASD Systems

Duan

Tang

et al. 2022

Sensors

View full text Add to dashboard Cite

The performance evaluation of state estimators for nonlinear regular systems, in which the current measurement only depends on the current state directly, has been widely studied using the Bayesian Cramér-Rao lower bound (BCRLB). However, in practice, the measurements of many nonlinear systems are two-adjacent-states dependent (TASD) directly, i.e., the current measurement depends on the current state as well as the most recent previous state directly. In this paper, we first develop the recursive BCRLBs for the prediction and smoothing of nonlinear systems with TASD measurements. A comparison between the recursive BCRLBs for TASD systems and nonlinear regular systems is provided. Then, the recursive BCRLBs for the prediction and smoothing of two special types of TASD systems, in which the original measurement noises are autocorrelated or cross-correlated with the process noises at one time step apart, are presented, respectively. Illustrative examples in radar target tracking show the effectiveness of the proposed recursive BCRLBs for the prediction and smoothing of TASD systems.

show abstract

“…Therefore, it is necessary to study new MTT algorithms for problems with coloured measurement noise. In the existing literature, the problem of state estimation with coloured measurement noise has been solved via the Kalman filter [34], consensus-based filter [35,36], and Gaussian approximation filter [37]. However, these algorithms are only suitable for single-target tracking, not for multitarget tracking.…”

Section: Introductionmentioning

confidence: 99%

Poisson multi‐Bernoulli mixture filters with coloured measurement noise

et al. 2022

IET Radar Sonar & Navi

View full text Add to dashboard Cite

To solve multitarget tracking (MTT) problems with coloured measurement noise, this study proposes a Poisson multi-Bernoulli mixture filter with coloured measurement noise (PMBM-CMN) and a robust PMBM-CMN filter. By using the measurement differencing method and state augmentation approach, the proposed PMBM-CMN filter transforms a state estimation problem with coloured measurement noise into a problem with white measurement noise. However, covariances of the true process and measurement noise in the proposed PMBM-CMN filter are time-varying and unknown, which may degrade the filtering performance. Therefore, a robust PMBM-CMN filter is proposed for estimating the augmented state, including the kinematic state, the predicted state covariance, and the white measurement noise covariance. For linear Gaussian systems, the augmented state is modelled as a Gaussian inverse Wishart inverse Wishart (GIWIW) distribution. The variational Bayesian method is also employed to guarantee the conjugacy of the GIWIW density. Simulation results demonstrate the ability of the PMBM-CMN filter to solve MTT problems with coloured measurement noise and show that the robust PMBM-CMN filter based on the GIWIW model (GIWIW-PMBM-CMN) has the best overall performance in comparison with existing state-of-the-art filters.

show abstract

Adaptive Consensus-Based Unscented Information Filter for Tracking Target with Maneuver and Colored Noise

Cited by 12 publications

References 34 publications

Accurately Tracking Hypersonic Gliding Vehicles via an LEO Mega-Constellation in Relay Tracking Mode

Accurately Tracking Hypersonic Gliding Vehicles via an LEO Mega-Constellation in Relay Tracking Mode

Bayesian Cramér-Rao Lower Bounds for Prediction and Smoothing of Nonlinear TASD Systems

Poisson multi‐Bernoulli mixture filters with coloured measurement noise

Contact Info

Product

Resources

About