Search results

The purpose of this study is to establish an effective tracking algorithm for small unmanned aerial vehicles (UAVs) based on interacting multiple model (IMM) to take timely countermeasures against illegal flying UAVs.

In this paper, based on the constant velocity model (CV), the maneuvering adaptive current statistical model (CS) and the angular velocity adaptive three-dimensional (3D) fixed center constant speed rate constant steering rate model, a small UAV tracking algorithm based on adaptive interacting multiple model (AIMM-UKF) is proposed. In addition, an adaptive robust filter is added to each model of the algorithm. The linear Kalman filter algorithm is attached to the CV model and the CS model and the unscented Kalman filter algorithm (UKF) is attached to the CSCDR model to solve the nonlinearity of the 3D turning model.

Monte-Carlo simulation comparison with the other two IMM tracking algorithms shows that in the case of different movement modes and maneuvering strength of the UAV, the AIMM-UKF algorithm makes a good trade-off between the amount of calculation and filtering accuracy, which can maintain more accurate and stable tracking and has strong robustness. At the same time, after testing the actual observation data of the UAV, the results show that the AIMM-UKF algorithm state estimation trajectory can be regarded as an actual trajectory in practical engineering applications, which has good practical value.

This paper presents a new small UAV tracking algorithm based on IMM and the advantages and practicability of this algorithm compared with existing algorithms are proved through experiments.

Marine exploration is becoming an important element of pervasive computing underwater target tracking. Many pervasive techniques are found in current literature, but only scant research has been conducted on their effectiveness in target tracking.

This research paper, introduces a Shifted Rayleigh Filter (SHRF) for three-dimensional (3 D) underwater target tracking. A comparison is drawn between the SHRF and previously proven method Unscented Kalman Filter (UKF).

SHRF is especially suitable for long-range scenarios to track a target with less solution convergence compared to UKF. In this analysis, the problem of determining the target location and speed from noise corrupted measurements of bearing, elevation by a single moving target is considered. SHRF is generated and its performance is evaluated for the target motion analysis approach.

The proposed filter performs better than UKF, especially for long-range scenarios. Experimental results from Monte Carlo are provided using MATLAB and the enhancements achieved by the SHRF techniques are evident.

A laser seeker is an important element in missile guidance and control systems, responsible for target detection and tracking. Its control is, however, a challenging problem due to complex dynamics and various acting disturbances. Hence, the purpose of this study is to propose a systematic design, tuning, analysis and performance verification of a nonlinear active disturbance rejection control (ADRC) algorithm for the specific case of the laser seeker system.

The proposed systematic approach of nonlinear ADRC application to the laser seeker system consists of the following steps. The complex laser seeker control problem is first expressed as a regulation problem. Then, a nonlinear extended state observer (ESO) with varying gains is used to improve the performance of a conventionally used linear ESO (LESO), which enables better control quality in both transient and steady-state periods. In the next step, a systematic observer tuning, based on a detailed analysis of the system disturbances, is proposed. The stability of the overall control system is then verified using a describing function method. Next, the implementation of the NESO-based ADRC solution is realized in a fixed-point format using MATLAB/Simulink and Xilinx System Generator. Finally, the considered laser seeker control system is implemented in discrete form and comprehensively tested through hardware-in-the-loop (HIL) co-simulation.

Through the conducted comparative study of LESO-based and NESO-based ADRC algorithms for the laser seeker system, the advantages of the proposed nonlinear scheme are shown. It is concluded that the NESO-based ADRC scheme for the laser seeker system (with appropriate parameters tuning methodology) provides better control performance in both transient and steady-state periods. The conducted multicriteria study validates the efficacy of the proposed systematic approach of applying nonlinear ADRC to laser seeker systems.

In practice, the obtained results imply that the laser seeker system, governed by the studied nonlinear version of the ADRC algorithm, could potentially detect and track targets faster and more accurately than the system based on the common linear ADRC algorithm. In addition, the article presents the step-by-step procedure for the design, field programmable gate array (FPGA) implementation and HIL-based co-simulation of the proposed nonlinear controller, which can be used by control practitioners as one of the last validation stages before experimental tests on a real guidance system.

The main contribution of this work is the systematic procedure of applying the ADRC scheme with NESO for the specific case of the laser seeker system. It includes its design, tuning, analysis and performance verification (with simulation and FPGA hardware). The novelty of the work is also the combination and practical realization of known theoretical elements (NESO structure, NESO parameter tuning, ADRC closed-loop stability analysis) in the specific case of the laser seeker system. The results of the conducted applied research increase the current state of the art related to robust control of laser seeker systems working in disturbed and uncertain conditions.

Continuous and stable tracking of the low-altitude maneuvering targets is usually difficult due to terrain occlusion and Doppler blind zone (DBZ). This paper aims to present a non-myopic scheduling method of multiple radar sensors for tracking the low-altitude maneuvering targets. In this scheduling problem, the best sensors are systematically selected to observe targets for getting the best tracking accuracy under maintaining the low intercepted probability of a multi-sensor system.

First, the sensor scheduling process is formulated within the partially observable Markov decision process framework. Second, the interacting multiple model algorithm and the cubature Kalman filter algorithm are combined to estimate the target state, and the DBZ information is applied to estimate the target state when the measurement information is missing. Then, an approximate method based on a cubature sampling strategy is put forward to calculate the future expected objective of the multi-step scheduling process. Furthermore, an improved quantum particle swarm optimization (QPSO) algorithm is presented to solve the sensor scheduling action quickly. Optimization problem, an improved QPSO algorithm is presented to solve the sensor scheduling action quickly.

Compared with the traditional scheduling methods, the proposed method can maintain higher target tracking accuracy with a low intercepted probability. And the proposed target state estimation method in DBZ has better tracking performance.

In this paper, DBZ, sensor intercepted probability and complex terrain environment are considered in sensor scheduling, which has good practical application in a complex environment.

This note aims to introduce a terminal guidance law that is able to compensate for evasive target maneuvers without estimating their acceleration.

The new guidance law is derived in the framework of linear-quadratic optimal control to ensure interception with minimum energy even in the presence of a target maneuver.

An explicit closed-form expression for the missile acceleration command is provided, which turns out to be a non-trivial extension of proportional navigation guidance. Simulation results against evasive maneuvers of various intensities are provided to compare the new law to classical ones and thus show the benefits of the proposed approach.

The proposed guidance law was not reported so far in the literature and provides a simple way to deal with evasive maneuvers.

The purpose of this paper is to demonstrate the theoretical relationship between the layout of four‐sensor dynamic acoustic array tracking system and systematic observation accuracy, and provide an algorithm to determine the optimal arrangement of four‐sensor acoustic array and an indicator to evaluate acoustic array system measurement accuracy.

In the present paper, the measurement principle of the four‐sensor dynamic acoustic array tracking system is analyzed, and the system observation model and the conversion relationship between models are established. Subsequently, the optimization algorithm for the four‐sensor dynamic acoustic array is deduced, the theoretical optimal arrangement of the four‐sensor dynamic acoustic array tracking measurement system is obtained based on the optimal position dilution of precision function (PDOPF) of 2D target, and the static experimental study on sound‐source bearing estimation is designed. The theoretical results are compared with the experimental results of the present study.

The measurement accuracy of the four‐sensor dynamic acoustic array tracking system is largely dependent on the layout of the acoustic sensor. Theoretical studies and experimental results demonstrated that an optimal PDPOF can be used to analyze the rationality of the layout. It can also serve as an indicator for the layout of the four‐sensor dynamic acoustic array tracking system.

The PDOPF value is presented as an indicator for the evaluation of the four‐sensor dynamic acoustic array systematic observation accuracy based on theoretical analysis. The feasibility of the indicator and the rationality of the sensor layout in practical engineering application are verified through experimental studies on sound‐source bearing estimation. The higher the PDOPF value is, the lower the accuracy of the system will be.

The paper aims at developing a novel algorithm to estimate high-order derivatives of rotorcraft angular rates to break the contradiction between bandwidth and filtering performance because high-order derivatives of angular rates are crucial to rotorcraft control. Traditional causal estimation algorithms such as digital differential filtering or various tracking differentiators cannot balance phase-lead angle loss and high-frequency attenuation performance of the estimated differentials under the circumstance of strong vibration from the rotor system and the rather low update rate of angular rates.

The algorithm, capable of estimating angular rate derivatives to maximal second order, fuses multiple attitude signal sources through a first-proposed randomized angular motion maneuvering model independent of platform dynamics with observations generated by cascaded tracking differentiators.

The maneuvering flight test on 5-kg-level helicopter and the ferry flight test on 230-kg-level helicopter prove such algorithm is feasible to generate higher signal to noise ratio derivative estimation of angular rates than traditional differentiators in regular flight states with enough bandwidth for flight control.

The decrease of update rate of input attitude signals will weaken the bandwidth performance of the algorithm and higher sampling rate setting is recommended.

Rotorcraft flight control researchers and engineers would benefit from the estimation method when implementing flight control laws requiring angular rate derivatives.

A purely kinematic randomized angular motion model for flight vehicle is first established, combining rigid-body Euler kinematics. Such fusion algorithm with observations generated by cascaded tracking differentiators to estimate angular rate derivatives is first proposed, realized and flight tested.

This study aims to investigate the rule‐based decentralised control framework for a swarm of UAVs carrying out a cooperative ground target engagement mission scenario.

This study is to investigate the rule‐based decentralised control framework for missions which require high‐level cooperation between team members. The design of the authors’ control strategy is based on agent‐level interactions. Different to a centralized task assignment algorithm, the cooperation of the agents is entirely implicit. The behaviour of the UAVs is governed by rule sets which ultimately lead to cooperation at a system level. The information theoretic measures are adopted to estimate the value of possible future actions. The prediction model is further considered to enhance the team performance in the scenario where there are tight coupled task constraints.

The simulation study evaluates the performance of the decentralised controller and compares it with a centralised controller quantitatively. The results show that the proposed approach leads to a highly cooperative performance of the group without the need for a centralised control authority. The performance of the decentralised control depends on the complexity of the coupled task constraints. It can be improved by using a prediction model to provide information such as the intentions of the neighbours that is not available locally.

The achievable performance of the decentralised control was considered to be low due to the absence of communication and little global coordinating information. This study demonstrated that the decentralised control can achieve highly cooperative performance. The achievable performance is related to the complexity of the coupled constraints and the accuracy of the prediction model.

The purpose of this paper is to improve the robustness of the traditional Bhattacharyya metric for the effect of histogram quantization in the histogram-based visual tracking. However, the traditional Bhattacharyya metric neglects the correlation of crossing-bin and is not robust for the effect of histogram quantization.

In this paper, the authors propose a visual tracking method via crossing-bin histogram Bhattacharyya similarity in the particle filter.

A crossing-bin matrix is introduced into the traditional Bhattacharyya similarity for measuring the reference histogram and the candidate histogram, and the basic tasks of measure such as maximum similarity of self and the triangle inequality are proven. The authors use the proposed measure in the particle filter visual tracking framework and address a model update strategy based on the crossing-bin histogram Bhattacharyya similarity to improve the robustness of visual tracking.

In the experiments using the famous challenging benchmark sequences, precision of the proposed method increases by 12.8 per cent comparing the traditional Bhattacharyya similarity and the cost time decreases by 38 times comparing the incremental Bhattacharyya similarity. The experimental results show that the proposed method can track the object robustly and rapidly under illumination change and occlusion.

This paper aims to propose a set of six-axis robot arm welding seam tracking experiment platform based on Halcon machine vision library to resolve the curve seam tracking issue.

Robot-based and image coordinate systems are converted based on the mathematical model of the three-dimensional measurement of structured light vision and conversion relations between robot-based and camera coordinate systems. An object tracking algorithm via weighted local cosine similarity is adopted to detect the seam feature points to prevent effectively the interference from arc and spatter. This algorithm models the target state variable and corresponding observation vector within the Bayes framework and finds the optimal region with highest similarity to the image-selected modules using cosine similarity.

The paper tests the approach and the experimental results show that using metal inert-gas (MIG) welding with maximum welding current of 200A can achieve real-time accurate curve seam tracking under strong arc light and splash. Minimal distance between laser stripe and welding molten pool can reach 15 mm, and sensor sampling frequency can reach 50 Hz.

Designing a set of six-axis robot arm welding seam tracking experiment platform with a system of structured light sensor based on Halcon machine vision library; and adding an object tracking algorithm to seam tracking system to detect image feature points. By this technology, this system can track the curve seam while welding.