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

2005/10/01 by X Rong Li, V.P. Jilkov, Vesselin P. Jilkov · 1,142 citations
Computer Science · Engineering · #Artificial intelligence #Computer science #Computer vision #Engineering #Fault Detection and Control Systems #Inertial Sensor and Navigation #Kalman filter #Motion (physics) #Radar #Radar tracker #Target Tracking and Data Fusion in Sensor Networks #Telecommunications #Tracking (education) #Tracking system #Underpinning

paper · doi:10.1109/taes.2005.1561886

published in IEEE Transactions on Aerospace and Electronic Systems 41(4), 1255-1321 (Institute of Electrical and Electronics Engineers)

openalex publication_date 2005/10/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Abstract

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.

Citations

• Kalman filter versus IMM estimator: when do we need the latter?
• Maximum likelihood estimates of linear dynamic systems
• Benchmark for radar allocation and tracking in ECM
• The interacting multiple model algorithm for systems with Markovian switching coefficients
• A tutorial on hidden Markov models and selected applications in speech recognition
• Survey of maneuvering targettracking . part I: dynamic models

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• Multiple model trajectory poisson multi-bernoulli mixtures filter for tracking multiple maneuvering objects. [europepmc]

Related

• Survey of maneuvering targettracking . part I: dynamic models
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