Showing papers by "National University of Defense Technology published in 1994"

Application of difference method to dim point target detection in infrared images

Abstract: This paper deals with the detection of dim point targets in infrared images. Dim point targets detection is always a difficulty in information processing. Researchers have proposed many effective methods in this aspect, this paper no longer mentions them but will introduce a new method. Whereas difference method has obtained good results in 1D signal processing, this paper manages to apply it to 2D signal processing, that is to say, dim point targets detection in infrared images of low SNR.

The application of difference method to dim point target detection in infrared images

Abstract: This paper deals with the detection of dim point targets in infrared images. Dim point targets detection is always a difficulty in information processing. Researchers have proposed many effective methods; this paper introduces a new method. Whereas difference method has obtained good result in one dimensional signal processing, this paper manages to apply it to two dimensional signal processing, that is to say, dim point targets detection in infrared images of low SNR. The image background is color noise, and its column correlation is strong. So, ordinary methods probably lose the true targets because of the strong color noise, but unlike them, difference method can overcome this shortcoming, it can eliminate correlation noise and enhance useful information, finally pick out the probable targets from noise background. In the paper, the method was given a more extensive account. In order to improve the detection effect, we utilize prefilter. The prefilter is realized by the alpha filter. Because the same targets have same location in more than three frames, using alpha filter can utilize the information of adjacent frames, increase the SNR of the raw data and reduce the noise of the images. >

Dim point target detecting from image sequences

Abstract: The technique of detecting and tracking of a moving point target is space-based background with low SNR is analyzed in this paper. An efficient method for detecting low speed targets is presented. The method simply uses multi-frame accumulating as the main operation in improving the output SNR. And it introduces candidate target records for target matching and recognition. The method is easy for hardware implementation that meets the demands of real time processing and low power consumption.

Radar target modeling and recognition based on scattering centers

Abstract: Based on the concept of scattering center and applying approximate scale relationship of back scattering signals in two near aspect angles, this paper adapts Mellin transform to reconstruct target's pattern and to overcome effectively problems of features extraction caused by the factor that scattering centers are sensitive to the changes of aspect angles. By using three scale aircraft targets, the recognition experimental study has been done. The results show that the method presented in the paper is effective and feasible. >

Detecting dim point target in infrared image sequences using probalilistic neural network

Abstract: In spite of many advances of IR imaging technology that have been achieved, the detection of dim point target from infrared clutter backgrounds still remains a key problem in real-time IR system. We present a new detection scheme based on a linear detector and an improved probabilistic neural network classifier for small SNR, moving point targets detection in strong infrared noise and clutter backgrounds. Computer simulation was conducted, and simulation results confirmed the validity of the detection scheme. >

Qualitative modeling based on fuzzy relation and its application

Abstract: This paper describes the method of modeling of multivariable dynamical systems based on fuzzy relation equation solving. Its application to economic cycle research and macroeconomic early warning is discussed. >

Detecting dim point targets in infrared image sequences using probabilistic neural networks

Abstract: In spite of many advances of IR imaging technology that have been achieved, the detection of dim point targets from IR clutter backgrounds still remains a key problem in real-time IR systems. We present a new detection scheme based on a linear detector and an improved probabilistic neural network classifier for small SNR, moving point targets detection in strong IR noise and clutter backgrounds. Computer simulation was conducted and simulation results confirmed the validity of the detection scheme.

The 3-D location and tracking of moving emitter using distance difference and azimuth measurements

Abstract: The paper presents a 3-D location and tracking algorithm based on the emitter's distance difference between two measurements and azimuth message. The location principle and feasibility of the method are analysed in detail. Under the condition that an emitter moves linearly at a constant speed, if we can locate and track an emitter only by using azimuth and distance difference without any angle of elevation, the equipment in the receiver will be simplified and the independence of the receiver may be improved as well. Then the algorithm proposed in the paper is of great importance to the practicability of the single observer passive location and tracking system. Performance of this algorithm is evaluated with the help of computer simulation test for three typical target paths. >

New Method for Determining the Shock Temperature of Metals

Abstract: Traditionally, shock temperature determination of metals needs to do a two-step calculation from the measured thermal radiation history. In this paper, however, we present some experimental events which make it possible to deduce the release temperature directly from the measured interface radiation history record.

Detecting and tracking of a moving point target in space-based background with low signal to noise ratio

Abstract: The technique of detecting and tracking of a moving point target in space-based background with low SNR is analysed in this paper. An efficient method for detecting low speed target is presented. The method simply uses multi-frame accumulating as the main operation to improve the output SNR. And it introduces candidate target records for target matching and recognition. The method is easy for hardware implementation that meets the demands of real time processing and low power consumption. >

The neural network method for radar weak target detection

Abstract: Because of the statistical nature nature of many types of clutter, a radar target detector must set a fairly high threshold in order to order to maintain a reasonable false-alarm rate. However, weak targets are usually missed for the above threshold detector. This paper presents an effective detector, which can be considered as a two-dimensional feature matching filter for radar signals. The feature extraction is performed by Hopfield neural networks and the feature integration is finished by a multilayer perceptron. In order to overcome the local optimum problem, a novel modification which is called energy comparing method is introduced into the Hopfield model dynamic equation to find the global optimum. By testing with the real radar return data in a low signal-to-clutter ratio, the detector presented in this paper has more advantages than the conventional threshold detector. >

A Historical Note on the Linear Elastic Law

Abstract: This article presents some records about the direct proportionality between force and displacement which were made by Zheng Xun, a Chinese, 1500 years prior to R. Hooke. Further analysis and comparison are also offered in the article.

High-order moments modeling algorithm of radar target impulse response

Abstract: A method for characterizing radar signatures using HOMM (high-order moments modelling) is developed based on the high-order moments theory. This method consists of extracting radar target natural resonant frequencies by estimating the model of the radar target impulse response. In this paper,we analysed UWB radar target impulse response using high-order moments character on the base of the singularity expanding method, and made use of the total least squares method coupled with singularity value decomposition to accurately estimate the parameters of a rational of the impulse response. >

Radar target recognition based on polarization features

Abstract: This paper studied the various polarization characteristics of the radar target. For applying more effectively the polarization information of the target, the paper presented a new radar target recognition method of multidimensional polarization features space. For three kind of aircraft, the multidimensional polarization feature space has been established, and the recognition experimental study has been done. The results show that the method of the radar target recognition presented in this paper is efficient and feasible. >

The reasonability conditions for the identical thresholds assumption in IID parallel distributed detection networks

Abstract: This paper proposed the reasonability conditions for identical thresholds assumption, which is widely adopted in the design of independent identical distributed (IID) detection networks. These conditions lay a theoretical foundation for the usually used design procedure. >

The effectivity analysis of approximate reasoning models in expert system

Abstract: In this paper,the entropy method is used as a well-suited tool to analyze the effectivity and stability of the reasoning models. We analyse two kinds of typical reasoning models: certainty theory and D-S theory. With the aid of the colony entropy, the effectivity and stability of models is studied by the convergence of entropy on the condition of intersupporting evidence. Moreover, we contrast two reasoning models in effectivity, stability and robustness. >

Wavelet transform approach to the feature extraction for incoherent radar ship target

Abstract: In this paper, a new approach to the feature extraction for incoherent radar ship target recognition is proposed, based on the discrete dynamic wavelet transform. Experiments are carried out for the method with practical video-echo data of four kinds. The corresponding results indicate that the extracted features are typical with high data compression.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.