The Study Of Weak Signal Detection Method Based On The Chaotic Oscillator's Geometry Characters

The researching of the weak signal detection is a comprehensive technology and cuspidate field in measurement technology under the background of noise. The technology of weak signal detection can help us to detect very weak signal that can not be detected normally and the measurement precision of weak signal can be raised. So it is the important method of developing new technology to find new principal. According to the developing history of the weak signal detection and estimation, it can be divided into two methods: one is time-domain method, and the other is frequency-domain method. Recently we found that The frequency-domain method should make suppose to signal and noise ahead of time, and because of this, it is limited in the practical application, Time-domain method is simple, ocular, obvious physics and easy to be realized with hardware. The weak signal measuring method based on chaos theory which is introduced in this paper is time-domain method too. The measuring of the weak sine signal is important in numerous weak signal measuring methods, so in this paper, we do the research of the weak sine signal detection emphatically.Chaotic phenomena widely exists in the nature, chaotic motion can describe the very typical behavior of many nonlinear systems, and chaotic system represents the characters that it is rather sensitive to regular weak signal but immune to noise, so chaos theory has raised many native and foreign scholars to pay extensive attention and do further research on it. An important application of chaos theory in information science is the information detection. A chaotic system is rather sensitive to regular signal but immune to noise, which make chaos have good prospect in information detection technique. Chaos detection for weak signals belongs to this technique, and although it is a new subject, it has already made a great progress, and will have a more great development. What will be discussed in this paper is a weak signal detection method which is based on the chaos theory, and the main research task of this paper is using nonlinear chaos oscillator to measure the weak sine signal which is deep embedded in the noise, and carry out the quantitative detection of the weak sine signal's amplitude.The weak signal detection based on the chaos theory is mainly use the system's character that the chaotic system is sensitive to the initial conditions, and a small signal can cause the essential change of the system's periodic solution. At present, using chaotic oscillator to detect weak signal mainly includes two methods: one is based on the changes of the phase diagram, and the other is based on the lyapunov exponent. The two methods all use the transition between the states of the system from the chaos to period and thus realize the weak signal detection.Although chaos theory has a very large development space, and also has got some achievements, it is easy to bring about such questions as: firstly, the critical value is not accurate. In the above-mentioned method, it is necessary to make certain the bifurcation threshold value of the chaotic critical state, but from now, there is not any analytical algorithm to present the value. In fact, the value is usually determined experimentally, from which, we only get the range of the value not accurate value. To solve this problem, we either choose a detection method that is independent of the critical value or find a new accurate approach to determine the critical value. Secondly, for the method based on the changes of the phase diagram, if the simulation time is not long enough, it is easy to cause a misjudgment, in other words, if we determine the state at the head of the simulation as a periodic state, but in the fact the system will change into the chaotic state, and of course, we will make a error judge, and as a result, the detection will fall into error. For the method based on the lyapunov exponent, though it is a criterion which can make sure the system is at the state of chaos or period accurately, the algorithm of calculating the lyapunov exponent is complicated, so in the practical application, this method hasn't had a extensive application. And these problems of chaos theory in application are the main content of this paper.In this paper, on the base of the traditional weak signal detection by using chaos theory, we develop the method of the state changing of the phase diagram, and propose a detection model which has two chaotic oscillators, according to the detection principle, we name the model as difference double chaotic oscillators. From the output of the difference double chaotic oscillators system in the time-domain, we can observe the system time-solution and the system's state vividly and in real-time, as a result, the detection model make the judge more exact and make the physical meaning more obviously, and in sum, the detection performance is nice.According the problems of the method based on the state changing of the phase diagram, in this paper we propose a new detection method, and we call it as a weak signal detection method based on the chaotic oscillator's geometry characters. The best advantage of this method is that in the process of detecting signal, we make the chaotic system at the period state all time. In the real detection, first we need to pick up the chaotic oscillator's geometry characters, and then build the relationship between the geometry and the parameter of the weak signal, and at last, we can get the amplitude of the weak sine signal. This method realizes the quantitative detection of the weak sine signal's amplitude in a real sense, and the detection performance is also very good, and more, comparing to the traditional chaotic signal detection, the detection principle of this method is so simple.In sum, measuring method introduced in this paper combines chaos theory and weak signal theory is better than any other time-domain measuring method, and at the same time, It is so simple, ocular, obvious physics and easy to be realized with hardware.