Zhongliang Jing

A selection algorithm for conflict aircrafts and performance analysis based on ADS-B

An algorithm based on ADS-B was proposed to meet the demand of collision avoidance for the complicated traffic situation of Free Flight. The algorithm selected the potential conflict aircrafts within 40-100 nm radius, which took advantages of abundant information and high updating rate of ADS- B. Function simulation was carried out using MATLAB, then Monte-Carlo method was used to analysis the efficiency of this algorithm. The results show that the algorithm has a good performance in selecting conflict aircrafts from secure aircrafts. The algorithm can be used as the pre-processing of the conflict probability prediction algorithm, which must be helpful to the safety of Free Flight in the future.

Adaptive maneuvering targets tracking for multiple airborne mobile platforms and sensors

The problem of adaptive maneuvering targets tracking for multiple airborne mobile platforms and sensors in a fusion system is considered. First, the maneuvering target dynamic state equation based on the current statistical model is presented. Then, in the environment of multiple airborne mobile platforms and sensors, the state and measurement equations of the maneuvering targets are deduced. Finally, the adaptive maneuvering target tracking algorithm is given. Monte-Carlo simulation shows that the algorithm produced in this paper can estimate the state of maneuvering targets effectively.

An improved ant colony optimization approach for multi-aircraft horizontal escape maneuvers

An improved ant colony optimization approach for multi-aircraft escape maneuvers in the horizontal plane was proposed in this paper. An ant colony algorithm is a typical cluster algorithm, which is a new application in aircraft traffic collision avoidance system. A multi-aircraft horizontal maneuver model based on ant colony algorithm was proposed. The right maneuver angle as probability value was selected as the optimization parameter in the ant colony approach, which is a preference angle. And multiple simulation results showed that the improved ant colony algorithm made a great progress than the basic ant colony algorithm, which with the minimum maneuver cost in conflict escape. This improved ant colony optimization approach can apply in the next generation TCAS in horizontal RAs.

Integrated Aircraft Environment Surveillance System for large civil aircraft

The paper presents the Integrated Aircraft Environment Surveillance System (IAESS) for large civil aircraft based on the federated ARJ21 Aircraft Environment Surveillance System (AESS) functional baseline and recent technology advances. The goal is to reduce life cycle cost, promote reliability and enhance functionality. Two different IAESS processing unit architectures are provided. Three fusion models for integrate those IAESS data based on information fusion technology were presented in this paper.

Visual analysis for 2-D point set matching

This paper presents a theoretically simple, yet efficient approach for the problem of matching the 2-D point sets under rigid motion, where jitter is allowed. It is a fundamental problem in pattern recognition, having applications ranging from robotics to astronautics. Commonly, the previous methods tend to use symbolic arithmetic to solve this problem. However, they are always complex and limited by computational cost. In this paper, we present a visual analysis for the point set matching problem and develop a geometrical arithmetic which is proven to yield equivalent results to the symbolic arithmetic. This allows us to view the problem as one of shape matching and obtain an algorithm that firstly generates a probabilistic shape descriptor (PSD) to describe the local geometric property of each point in the point sets, then acquires the local correspondence from the Euclidean distance matrix of the descriptors, and validates the global transformation finally. Experimental results demonstrate that our simple algorithm with a lower computation complexity effectively improves accuracy over current method, particularly when matching equal-size patterns under varying jitter.

Robust adaptive trajectory linearization control for a class of uncertain nonlinear systems

This paper presents a novel robust adaptive trajectory linearization control (RATLC) method for a class of uncertain nonlinear systems based on a single hidden layer neural networks disturbance observer (SDO). The term ldquodisturbancerdquo used in this paper refers to the combination of model uncertainties and external disturbances. By utilizing the universal approximation property of neural networks with useful information on the controlled plant, the SDO can monitor time-varying disturbance very well. A robust adaptive term is added to overcome reconstruction error. Conditions are derived which guarantee ultimate boundedness of all the errors in the combined system. Excellent disturbance attenuation ability and strong robustness of the proposed RATLC method are demonstrated by an example of inverted pendulum control problem.

A new robust adaptive trajectory linearization control scheme for uncertain nonlinear systems

This paper presents a novel robust adaptive trajectory linearization control (RATLC) method for a class of uncertain nonlinear systems using radial basis function neural networks (RBFNN). TLC is a promising nonlinear tracking and decoupling control method, which has experienced growing interests and popularity recently. However it may exhibit poor performance when uncertainties exist and turn large. Radial basis function neural networks are introduced to approximate the uncertainties online from available measurements. A robust adaptive signal is added to compensate for the estimation error of the neural network output. Conditions are derived which guarantee ultimate boundedness of all the errors in the combined system. Excellent disturbance attenuation ability and strong robustness of the proposed RATLC method are demonstrated by an numerical example.

An Optimal Color Image Fusion Approach Based on Quantitative Evaluation Indexes

The fusion technology of multi-sources images is important for spatial information applications, such as digital city. In order to keep the spectral information and spatial information in the process of multi-sources spatial images fusion, an optimal image fusion method based on quantitative evaluation indexes is proposed in this paper. In IHS (intensity, hue and saturation) transform space, the feature image of high frequency of intensity component I is fused with multi-resolution wavelet. And the low frequency of intensity component I is fused on pixel level with optimal weight coefficients. Spectral information index ESP and spatial resolution index AG are used to adjust the fusion rule and achieve the optimum weight. The test results with QuickBird data show the effectiveness of presented method

Analysis and simulation of passive target tracking algorithm under polar coordinates

Due to the inborn non-linearity and observability problem, passive tracking is more difficult than active tracking, and the conventional algorithms cannot be applied to passive tracking directly. First, a brief review of the research work conducted on observability is given, then a traditional passive tracking algorithm under polar coordinates and its deficiencies are analyzed. A target maneuver detector is added to the traditional passive tracking algorithm and Monte-Carlo simulation shows that the proposed algorithm could successfully track objects moving with piece-wise constant velocity. Finally, future research areas are pointed out.

An Effective Algorithm for Tracking Multiple Maneuvering Targets

Multiple maneuvering target tracking in a dense clutter environment is investigated. An effective parallel processing algorithm based on state fusion and fast joint probabilistic data association (FJPDA) is proposed. State fusion and feedback of all state information are used to fit different movements of targets. The FJPDA combining cluster matrix decomposition with fast data association algorithm is built for tracking multiple targets. Two examples are simulated to prove the validity and reliability of the proposed new algorithm.Copyright