A Survey on Nonlinear Kalman Filtering under Communication Resource Constraints: Methods and Scheduling Strategies

In practical engineering applications, systems governed by nonlinear dynamics are widespread, and their inherent complexity has made the study and development of high-performance filtering methods an important and active research topic. This issue becomes particularly prominent in networked control systems. By leveraging distributed sensing and cooperative operation, networked control systems can improve overall system performance; however, under networked communication environments, their distributed architectures and inherent resource limitations further increase the difficulty of nonlinear filter design. This paper presents a systematic review of resourceefficient nonlinear Kalman filtering for networked control systems. First, mainstream nonlinear Kalman filtering methods are classified, and the characteristics of typical communication resource constraints in networked environments are analyzed. Then, representative strategies for alleviating communication bottlenecks are summarized and examined, including event-triggered mechanisms, encoding-decoding schemes, and sensor scheduling mechanisms. On this basis, recent advances in nonlinear Kalman filtering methods that explicitly incorporate the aforementioned resource-aware mechanisms into the filter design process are reviewed. Furthermore, the interactions among different constraint-handling techniques are discussed, and their combined effects on filtering performance are evaluated. Finally, several open issues in this field are highlighted, such as security assurance under resource-constrained conditions and adaptability to time-varying network environments, and several promising directions for future research are outlined.