Performance Evaluation In Automatic Target Recognition

Automatic Target Recognition (ATR) has great value not only in theory but also in application, for a long time, performance evaluation of this technology is very limited, now, performance evaluation becomes the most important problem that should be solved urgently. This direction is chosen as the focus of the thesis. We arrange the content aiming at the performance evaluation of Radar Target Recognition.Under analyzing the problem thoroughly, we present an creative idea in sum: on the basis of depicting the environment in quantity, study some key indexes, draw a quantitative result through object, effective performance evaluation model. The model must be universal and can be applied in engineer directly. The work is divided into some parts:Firstly, we find the scheme and arrange the work.Secondly, selecting some measurements to describe the environment for ATR system, as is to say in the article, offering the reference information for performance evaluation. The reference information here can be acquired and measured easily, and give objective result.In the third step, we give the concept called measurement of recogmtion rate (MRR). From the characteristics of MRR, a succession of evaluation indexes is educed. We have established the system of performance indexes. Here, Such problem as sample capacity's analytic solution, presenting the confidence extent of the evaluation conclusion, manipulating the level of two kinds of risk by different sample capacity, independence test between the recognition result and the environment, designing an experiment according to certain require are solved in a centralized, systemic and effective way.Subsequently, some evaluation model is developed based on different mathematics theory.1. We admit fuzzy comprehensive evaluation into ATR performance evaluation successfully; some evaluation models were built in conformity to different application. The key problems are settled like forming evaluation index in performance evaluation of multi-target recognition, selection of factor set, the eduction of evaluation matrix and multi-step fuzzy comprehensive evaluation. In order to avoid improper conclusion when the performance of thesystem being evaluated has changed, we perfect the weight-variable fuzzy comprehensive evaluation in existence; as a result, the performance evaluation model based on weight-variable fuzzy comprehensive evaluation is formed.During the evaluation course, the experimenter may need to settle the weight set in some situation; we advance an iterative method to work the fuzzy relation equation, on the basis of some ways in fuzzy mathematics.2. We can draw a concise result by fuzzy integration, so, performance evaluation model based o n fuzzy i ntegration i s c onstructed. We p robe t he m ethod tow ork o ut t he j udgement vector. Aiming at the deficiency of fuzzy integration in application, we put forward multi-layer fuzzy integration, then, establish an evaluation model with it. The modified multi-layer fuzzy integration is able to manage multi measurable function and their possibility measure; it can be used in dealing with complex problem directly in practice. The self-study in this kind of model is resolved.3. We study the technique to draw fuzzy resemble matrix between the objects being evaluated and fuzzy resemble matrix between different elements in the comment set; so, these means can be used in our work. Performance evaluation model based on fuzzy cluster analysis is built. It can be used to evaluate multi systems at one time quickly and draw useful conclusion.4. Performance evaluation with the help of fuzzy run theory. In order to remedy the information loss in Mini-Max operation that is included in fuzzy comprehensive evaluation, we found fuzzy run theory. It works with bottom run, variation in bottom run, and run between different dimensions, as desired by us, it analysis the information contained in the judgement matrix comprehensively. In consequence, this theory is used in work, and is illustrated through some examples.5. The fuzzy comprehensive methods may lose information in recognition results, at the same time, it can not get continuing output while the recognition result is changing in continuing way. We form some variable from the recognition result based on measure theory; in consequence, the evaluation model has been built.6. For an ATR system, it is of great importance that the performance can be stable while the situation is changing appreciably. We find the dynamic relation model of ATR system to the situation, then, with the help of Lyapunov theory, the stable condition is discussed.In addition, we analysis some typical factors related to ATR system, the equation of reference information is found.Finally, we carry out performance evaluation simulation to four ATR algorithms by the help of test data and synthesis data. It is proved by the simulation mat the idea of our work is right; the performance evaluation model can be used in practice directly, it have some characteristics: l)the result is objective, quantitive, and reflects most aspects of the recognition performance; 2)the situation is admitted in the evaluation model; 3)it can be used under a certain environment to make static state evaluation and stability evaluation, at the same time, it can be applied under changing environment to draw a dynamic evaluation; the variation interval can be all over the definition field or part of it; 4)it can compare systems in same design as well as in different design; 5)the performance model is a opening model, it can be configured according to the content being considered.From the data obtained, this is the first time to form a general quantified performance evaluation system in ATR.