신효상 교수

Proliferation of low-cost, lightweight, and power efficient sensors and advances in networked systems enable the employment of multiple sensors. Distributed estimation provides a scalable and fault-robust fusion framework with a peer-to-peer communication architecture. For this reason, there seems to be a real need for a critical review of existing and, more importantly, recent advances in the domain of distributed estimation over a low-cost sensor network. This paper presents a comprehensive re

This paper develops a new three-dimensional (3-D) guidance law which guarantees the interception of manoeuvring targets in a finite time. The new guidance law accepts the concept that nullifying the line-of-sight rate guarantees the interception of the target and its derivation is based on finite time sliding mode guidance. By using a 3-D kinematic equation set constructed in a rotating coordinate system, the proposed guidance law alleviates an issue of general 3-D guidance caused by the cross c

This article proposes an improved version of 3-D pure proportional navigation (PPN) against a manoeuvring target. The main research hypothesis is that the performance of 3-D PPN can be improved by properly selecting the direction of the guidance command as there exists an infinite number of potential directions complying with the PPN concept in 3-D space. Analysis on the relative motion confirms the validity of the hypothesis and leads to the development of a new guidance algorithm. Unlike tradi

Abstract Unmanned aerial vehicles, can offer solutions to a lot of problems, making it crucial to research more and improve the task allocation methods used. In this survey, the main approaches used for task allocation in applications involving UAVs are presented as well as the most common applications of UAVs that require the application of task allocation methods. They are followed by the categories of the task allocation algorithms used, with the main focus being on more recent works. Our ana

This paper proposes a novel joint probabilistic data association (JPDA) filter for joint target tracking and track maintenance under unknown detection probability and clutter rate. The proposed algorithm consists of two main parts: (1) the standard JPDA filter with a Poisson point process birth model for multi-object state estimation; and (2) a multi-Bernoulli filter for detection probability and clutter rate estimation. The performance of the proposed JPDA filter is evaluated through empirical

In this paper, nonlinear model predictive control (NMPC) is addressed to develop formation guidance for multiple unmanned aerial vehicles. An NMPC algorithm predicts the behavior of a system over a receding time horizon, and the NMPC generates the optimal control commands for the horizon. The first input command is, then, applied to the system and this procedure repeats at each time step. The input constraint and state constraint for formation flight and inter-collision avoidance are considered

This paper proposes a new distributed multiple model multiple manoeuvring target tracking algorithm. The proposed tracker is derived by combining joint probabilistic data association (JPDA) with consensus-based distributed filtering. Exact implementation of the JPDA involves enumerating all possible joint association events and thus often becomes computationally intractable in practice. We propose a computationally tractable approximation of calculating the marginal association probabilities for

Conflict Detection and Resolution (CD&R) for Unmanned Aerial Vehicles (UAVs) has become important consideration with remarkable development of sensor technology and autonomous control system. Since CD&R deals with safety of UAVs and aircraft, it has to be validated by rigorous analytical verification. This paper investigates the application of differential geometry to UAV CD&R algorithm for non-cooperating intruders such as static and dynamic obstacles. Two-dimensional geometry is used to detect

The capturability of the Three-Dimensional (3D) Realistic True Proportional Navigation (RTPN) guidance law is thoroughly analyzed. The true-arbitrarily maneuvering target is considered, which maneuvers along an arbitrary direction in 3D space with an arbitrary but upper-bounded acceleration. The whole nonlinear relative kinematics between the interceptor and target is taken into account. First, the upper-bound of commanded acceleration of 3D RTPN is deduced, using a novel Lyapunov-like approach.

This paper investigates the problem of distributed state estimation over a low-cost sensor network and proposes a new sample greedy gossip distributed Kalman filter. The proposed algorithm leverages the information weighted fusion concept and the sample greedy gossip averaging protocol. By introducing a stochastic sampling strategy in the greedy sensor node selection process, the proposed algorithm finds a suboptimal communication path for each local sensor node during the process of information

The operation of UAV swarms has attracted great attention as their coordination and cooperation could bring significant impact in both military and civilian applications. Despite this potential, there are key challenges to be addressed to enable UAV swarm operations. Unlike operations of a small number of aerial vehicles, the onboard decision‐making responsibility may be more favorably distributed across the UAV swarm taking into account their scalability and sustainability. This chapter address

This paper addresses the problem of maneuver recognition and behavior anomaly detection for generic targets by means of pattern matching techniques. The problem analysis is performed making specific reference to moving vehicles in a multi-lane road scenario, but the proposed technique can be easily extended to significantly different monitoring contexts. The potential extensions include, but are not limited to, public surveillance in train station or airport, road incidents and relative precurso