Radar sensor network resource allocation for fused target tracking: A brief review

Information Fusion, Год журнала: 2022, Номер 86-87, С. 104 - 115

Опубликована: Июнь 29, 2022

Traditional networked radar fusion technology adopts an open-loop signal processing manner, in which multiple nodes independently detect or track target first, and then send their raw data processed measurements to the center for state estimation. In such a working each sensor operates within predetermined rules, fixed transmit receiving mode changeable tracking environment, thus will definitely cause insufficient use of its limited resource. Resource allocation (RA) has emerged as promising exploit resource more efficient way by allocating available parameters w.r.t. collaboratively view fused performance. The goal this paper is provide brief overview RA methods network. We mainly investigate existing works divide them into two types, namely quality constrained type performance driven type. Solution techniques both types appeared literatures are also summarized. Finally, some potential future research directions field discussed.

Язык: Английский

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Multi-UAV Optimal Mission Assignment and Path Planning for Disaster Rescue Using Adaptive Genetic Algorithm and Improved Artificial Bee Colony Method

Actuators, Год журнала: 2021, Номер 11(1), С. 4 - 4

Опубликована: Дек. 28, 2021

An optimal mission assignment and path planning method of multiple unmanned aerial vehicles (UAVs) for disaster rescue is proposed. In this application, the UAVs include drug delivery UAV, image collection communication relay UAV. When implementing modeling simulation, first, three threat sources are built: weather source, transmission tower upland source. Second, a cost-revenue function constructed. The flight distance, oil consumption, descriptions source factors above considered. analytic hierarchy process (AHP) utilized to estimate weights function. Third, an adaptive genetic algorithm (AGA) designed solve allocation task. A fitness which considers current maximum iteration numbers proposed improve AGA convergence performance. Finally, plan between neighboring points computed by improved artificial bee colony (IABC) method. balanced searching strategy developed modify IABC computational effect. Extensive simulation experiments have shown effectiveness our

Язык: Английский

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Aspects of unmanned aerial vehicles path planning: Overview and applications

International Journal of Communication Systems, Год журнала: 2021, Номер 34(10)

Опубликована: Апрель 21, 2021

Summary Aiming to the applications from security surveillance, military operational capabilities content and package delivery, unmanned aerial vehicles (UAVs) has a successfully created his space in available technologies. The compact sized powerful flying robots are wirelessly controlled capable complete tasks with without direct human intervention. UAVs however still face serious challenges that limit dream of autonomous machines. key include path planning obstacle avoidance these unavoidable while performing application‐specific functionalities both indoor outdoor environments. In this manuscript survey, we investigate state‐of‐the‐art UAV algorithms techniques. We have also summarized compared schemes tabular form. addition, current future research directions discussed, showing prospective directions.

Язык: Английский

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Decomposed POMDP Optimization-Based Sensor Management for Multi-Target Tracking in Passive Multi-Sensor Systems

IEEE Sensors Journal, Год журнала: 2022, Номер 22(4), С. 3565 - 3578

Опубликована: Янв. 6, 2022

This paper presents an efficient information-theoretic sensor management method to maximize the performance of passive multi-sensor system for multi-target tracking. We model state as a generalized labeled multi-Bernoulli (GLMB) random finite set and formulate dynamic selection process partially observable Markov decision (POMDP). The optimization objective is maximum information gain obtained from observed data, which measured by Cauchy-Schwarz divergence. accomplished with two main technical innovations. first tractable decomposed POMDP based solution, in informative sensors are selected sequentially candidates on second novel dual-stage fusion strategy iterated-corrector GLMB filter. Since uncertainty generally large, scheme can be greatly influenced order updates. To fix this problem, ranked divergence selection, followed update. For fusion, effect poor weakened that better enhanced. Simulation studies demonstrate effectiveness efficiency proposed challenging tracking scenarios.

Язык: Английский

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Nonsingular Terminal Sliding Mode-Based Direct Yaw Moment Control for Four-Wheel Independently Actuated Autonomous Vehicles

IEEE Transactions on Transportation Electrification, Год журнала: 2022, Номер 9(2), С. 2568 - 2582

Опубликована: Окт. 5, 2022

This article introduces an accurate, robust, and efficient direct yaw-moment control (DYC) architecture for four-wheel independently actuated (FWIA) autonomous vehicles via the nonsingular terminal sliding mode (NTSM) method. To improve DYC performance of FWIA path tracking under critical maneuvers, a more accurate vehicle lateral dynamics model that considers tire nonlinear mechanics combined conditions is established first. On this basis, method based on phase plane theory introduced to analyze stability, two optimal external yaw moments are calculated by using NTSM algorithm takes reference rate sideslip angle as objectives, respectively. Then, moment finally applied weighting values, weight coefficient optimized in real time particle swarm optimization according instability analysis results. A real-time fast torque distribution further proposed achieve target moment, which force saturations, adaptive each wheel, partial derivative function involved. Simulation results are, finally, provided verify effectiveness controller improving stability four extreme eliminating steady errors angle.

Язык: Английский

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UAV penetration mission path planning based on improved holonic particle swarm optimization

Journal of Systems Engineering and Electronics, Год журнала: 2023, Номер 34(1), С. 197 - 213

Опубликована: Янв. 2, 2023

To meet the requirements of safety, concealment, and timeliness trajectory planning during unmanned aerial vehicle (UAV) penetration process, a three-dimensional path algorithm is proposed based on improved holonic particle swarm optimization (IHPSO). Firstly, terrain threat, radar detection, time in process UAV are quantified. Regarding threats, echo analysis method cross section (RCS) spatial situation to quantify concealment penetration. Then structure-particle (PSO) from three aspects. First, conversion ability search strategy enhanced by using system clustering information entropy grouping instead random constructing state switching conditions fitness function. Second, unclear setting iteration numbers addressed spacing create termination condition algorithm. Finally, optimized intended building predictive control model IHPSO for simulation verification. Numerical examples show superiority over existing PSO methods.

Язык: Английский

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Multi-UAV Collaborative Trajectory Optimization for Asynchronous 3-D Passive Multitarget Tracking

IEEE Transactions on Geoscience and Remote Sensing, Год журнала: 2023, Номер 61, С. 1 - 16

Опубликована: Янв. 1, 2023

This article considers the 3-D collaborative trajectory optimization (CTO) of multiple unmanned aerial vehicles to improve multitarget tracking performance with an asynchronous angle arrival measurements. The predicted conditional Cramér–Rao lower bound is adopted as a measure predict and subsequently control error online. Then, CTO problem cast time-varying nonconvex subjected constraints arising from dynamic security (height, collision, obstacle/target/threat avoidance). Finally, comprehensive solution method (CSM) presented tackle resulting problem, according its unique structures. Specifically, if all are inactive, can be simplified convex constraints, which solved by nonmonotone spectral projected gradient (NSPG) method. Oppositely, alternating direction penalty (ADPM) solve some positive constraints. ADPM introduces auxiliary vectors decouple complex separates into several subproblems tackles them alternately, while locally adjusting factor at each iteration. We show subproblem w.r.t. position vector but efficiently NSPG separable have closed-form solutions. Simulation results demonstrate that CSM outperforms unoptimized in terms performance. Besides, achieves near-optimal provided genetic algorithm much computational complexity.

Язык: Английский

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Linear Complexity Gibbs Sampling for Generalized Labeled Multi-Bernoulli Filtering

IEEE Transactions on Signal Processing, Год журнала: 2023, Номер 71, С. 1981 - 1994

Опубликована: Янв. 1, 2023

Generalized Labeled Multi-Bernoulli (GLMB) densities arise in a host of multi-object system applications analogous to Gaussians single-object filtering. However, computing the GLMB filtering density requires solving NP-hard problems. To alleviate this computational bottleneck, we develop linear complexity Gibbs sampling framework for computation. Specifically, propose tempered sampler that exploits structure achieve an $\mathcal{O}(T(P+M))$ complexity, where $T$ is number iterations algorithm, $P$ and $M$ are hypothesized objects measurements. This innovation enables filter implementation be reduced from $\mathcal{O}(TP^{2}M)$ $\mathcal{O}(T(P+M+\log T)+PM)$. Moreover, proposed provides flexibility trade-offs between tracking performance load. Convergence established, numerical studies presented validate implementation.

Язык: Английский

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Information-Seeking Sensor Selection for Ocean-of-Things

IEEE Internet of Things Journal, Год журнала: 2020, Номер 7(10), С. 10072 - 10088

Опубликована: Май 5, 2020

We propose a general sensor selection (SS) methodology for ocean-of-things (OoT) where sensing network performs multiobject tracking (MOT) under resource constraints. SS methods address the combinatorial problem of determining best subset sensors that maximizes suitable reward function fixed cardinality. The novelty this article is twofold. First, we tractable information-theoretic MOT-OoT with an unknown and time-varying number objects such as ocean vessels. A essential in order to rapidly evaluate subset, which crucial high-dimensional problems encountered OoT. Second, cross-entropy (CE-SS) efficiently estimates probabilities activations determines optimal according proposed imposed cardinality constraint. CE-SS algorithm avoids exhaustive searching over space all subsets, intractable most OoT applications. methodology, coupled function, capable selecting lead more accurate than random both vessels their trajectories. demonstrate effectiveness our method via numerical simulation serveral scenarios, including multivessel emulated acoustic deployed off coast Italy.

Язык: Английский

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Sensor Management for Search and Track Using the Poisson Multi-Bernoulli Mixture Filter

IEEE Transactions on Aerospace and Electronic Systems, Год журнала: 2021, Номер 57(5), С. 2771 - 2783

Опубликована: Март 3, 2021

A sensor management method for joint multitarget search and track problems is proposed, where a single user-defined parameter allows tradeoff between the two objectives. The density propagated using Poisson multi-Bernoulli mixture filter, which eliminates need separate handling of undiscovered targets provides theoretical foundation unified method. Monte Carlo simulations scenarios are used to evaluate performance proposed

Язык: Английский

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