Adaptive underwater target tracking using passive multipath time-delay measurements

Moose, R.; Dailey, T.

doi:10.1109/tassp.1985.1164665

Cited by 50 publications

(11 citation statements)

References 11 publications

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“…However, in several cases, practitioners may not have time stamping and hence the extent of delay remains unknown. Such delays are often known as random delay and appear in many domain of engineering, namely control [25], communication [26], aerospace [27]. The random delays in measurements lead to information loss and impact the estimation accuracy adversely.…”

Section: Tcqkf For a System With Delayed Measurementsmentioning

confidence: 99%

Transformed cubature quadrature Kalman filter

Singh

Bhaumik

2017

IET signal process.

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An orthogonal transformation is applied to the cubature quadrature (CQ) points which are used to approximate the intractable integrals appeared during the estimation of states of a non-linear system. With the help of a theorem, it is shown that the transformed points reduce the higher order moments (HOM) appeared while approximating the mean and covariance. As the HOM act as residue, the proposed method results in an improved filtering accuracy. Further, the proposition is extended in delayed measurement environment. The proposed method has been implemented for two different simulation problems. The simulation results reveal that at the same computational load, the filter with transformed CQ points provides higher accuracy compared with the filter with ordinary CQ points. The performance has been verified in the delayed measurement environment and an improved accuracy has been reported.

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Section: Tcqkf For a System With Delayed Measurementsmentioning

confidence: 99%

Transformed cubature quadrature Kalman filter

Singh

Bhaumik

2017

IET signal process.

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“…By quantizing the unknown input into several known levels, the GPB1 algorithm reduces to a single Kalman filter with a probabilistically weighted input for a linear target motion. Submarine tracking was studied further in [262], [263], [261], and [264] by GPB1 tracking in range, velocity, and depth using passive time delay measurements. References [123] and [266] presented detailed GPB1 designs for realistic scenarios of 3D manned maneuvering aircraft tracking.…”

Section: ) Surveillance For Air Traffic Controlmentioning

confidence: 99%

Survey of maneuvering target tracking. part v: multiple-model methods

Jilkov

2005

IEEE Trans. Aerosp. Electron. Syst.

841

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This is the fifth part of a series of papers that provide a comprehensive survey of techniques for tracking maneuvering targets without addressing the so-called measurement-origin uncertainty. Part I and Part II deal with target motion models. Part III covers measurement models and associated techniques. Part IV is concerned with tracking techniques that are based on decisions regarding target maneuvers. This part surveys the multiple-model methods-the use of multiple models (and filters) simultaneously-which is the prevailing approach to maneuvering target tracking in recent years. The survey is presented in a structured way, centered around three generations of algorithms: autonomous, cooperating, and variable structure. It emphasizes the underpinning of each algorithm and covers various issues in algorithm design, application, and performance.

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“…In recent decades, multiple new techniques have been applied to underwater tracking systems in the literature. Among various underwater tracking methods, the passive target tracking methods have attracted great interest [ 1 , 2 , 3 , 4 , 5 ] by the research community. Compared to the active system, the costs of operation and maintenance for passive systems are lower [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Underwater 3D Doppler-Angle Target Tracking with Signal Time Delay

Ali

et al. 2020

Sensors

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The traditional target tracking is a process of estimating the state of a moving target using measurement information obtained by sensors. However, underwater passive acoustic target tracking will confront further challenges, among which the system incomplete observability and time delay caused by the signal propagation create a great impact on tracking performance. Passive acoustic sensors cannot accurately obtain the target range information. The introduction of Doppler frequency measurement can improve the system observability performance; signal time delay cannot be ignored in underwater environments. It varies with time, which has a continuous negative impact on the tracking accuracy. In this paper, the Gauss–Helmert model is introduced to solve this problem by expanding the unknown signal emission time as an unknown variable to the state. This model allows the existence of the previous state and current state at the same time, while handling the implicit equations. To improve the algorithm accuracy, this paper further takes advantage of the estimated state and covariance for the second stage iteration and propose the Gauss–Helmert iterated Unscented Kalman filter under a three-dimensional environment. The simulation shows that the proposed method in this paper shows superior estimation accuracy and more stable performance compared with other filtering algorithms in underwater environments.

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Adaptive underwater target tracking using passive multipath time-delay measurements

Cited by 50 publications

References 11 publications

Transformed cubature quadrature Kalman filter

Transformed cubature quadrature Kalman filter

Survey of maneuvering target tracking. part v: multiple-model methods

Underwater 3D Doppler-Angle Target Tracking with Signal Time Delay

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