弱目标检测

2Harbin Institute of Technology 3University of Science and Technology of China
Abstract-A detection method based on the strong low-frequency weak-signal detection ability of stochastic resonance is proposed, aimed at the detection of the unknown weak signal. By mixing the unknown signal with a continuous linear changing local oscillator signal, a difference frequency signal will be generated, which will be sent to the stochastic resonance system. Thus, an obviously changed output can be obtained. Because the stochastic resonance system is extremely sensitive to low frequency, the system will have a maximum output when the local oscillator and frequency of the unknown signal are closest. The frequency of the unknown signal will be measured precisely from the local oscillator frequency and the difference frequency. It can be inferred from the theoretical analysis and numerical simulation that this method has a large detection range, high resolution, and good prospect.
In the past, the weak signal detection in general focused on the methods of reducing noise to improve the signal to noise ratio (SNR), but often damaging the actual signal in the process of suppressing noise. Stochastic resonance (SR) in this bistable system can take advantage of the noise energy to improve the signal detection capability. But stochastic resonance can only be used for the low frequency signals, thus, its utility has limited application[1-2]. In this paper, the frequency range of
The concept of stochastic resonance was put forward by the Italian physicist Roberto Benzi, American physicist Alfonso Sutera and Italian physicist Angelo Vulpoiani in the study of ancient meteorological glaciers in 1981 [1].
and Superhet Technology
12Shuo Shi, 12Wanyi Yin, 12Mingchuan Yang, 3Mingjie He 1National Key Laboratory of Communication System and Information Control Technology
Ⅲ. LIMITATIONS OF STOCHASTIC RESONANCE FREQUENCY DETECTION
the adiabatic approximation theory and linear response theory, the various effect of noise generated in the non-linear conditions are revealed[7-8]. The power spectrum of non-linear bistable system consists of two parts, one is caused by sinusoidal signal which has the same frequency of the input signal; the other one is caused by noise, and it has the form of Lorentz distribution. The power spectrum of Lorentz distribution present its noise characteristics of spectral energy concentrated to the low frequency region, therefore, the band of stochastic resonance spectrum peak will be limited in low frequency. When ������ > 1, it will deviate from the adiabatic approximation theory, and the increase of frequency leads to a lag in the system response. Because of this much larger range of signal-driven is needed to generate the stochastic resonance, therefore, stochastic resonance system is only suitable for low frequency (������ ≪ 1) signal detection[9].
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978-1-4673-2699-5/12/$31.00 © 2012 IEEE
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,
and
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be determined by the initial state. The signal and noise that are gradually increased or adjusted; the shape parameters cause the potential well to form, and this makes the particles go back and forth between the two potential wells. Since the potential difference between the potential wells of the bistable systems is much larger than the amplitude of the signal input, it makes the amplitude of the output signal far larger than the input. So the input signal is amplified effectively. Meanwhile, effectively suppressing the noise in the system output, transferring less energy of noise into signal, and enhances the SNR[4].
Key works: weak signals, stochastic resonance, superhet technology
Ⅰ. INTRODUCTION
Compared with noise, the amplitude of a signal is weak; the signal is completely submerged in the noise. On signal detection, the detection of the particular frequency is the most important.
detection of stochastic resonance system is discussed and recommendations are made for a high-frequency weak signal detection method.
Ⅱ. THE PRINCIPLE OF STOCHASTIC RESONANCE
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Fig.1 The potential curve of non-linear bistable system and the transitions of particle between the two potential wells
When there is no signal and noise input, the equation represents a system of two symmetric potential
wells, the central barrier height ∆������ = ������2 , two stable
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(1)
In equation (1), a,b are a real numbers representing the shape parameters of the potential well (In figure1, ������ = 1, ������ = 1 ). ������ ������ = ������������������������ 2������������0������ , ������(������) is the Gaussian white noise. Among them. ������ is amplitude of signals, ������0 is modulation frequency. The potential function of a bistable system is shown as follows.
Stochastic resonance describes the phenomenon of back and forth transition between noise and the periodic signal, in non-linear bistable system under overdamped Brownian particle motion[4]. The potential curve of the non-linear bistable system and the transitions curve of particlse between the two potential wells is shown in Fig.1. x(t) is the position of the output particles at any time, and this introduces the equation describing the particle motion-Langevin equation[5-6].
2012 7th International ICST Conference on Communications and Networking in China (CHINACOM)
A High-resolution Weak Signal Detection
Method Based on Stochastic Resonance