Study on detection of small-sized range-spread target by using chaotic Duffing oscillator

Xiaoying Deng, Haibo Liu, Li Wang, T. Liu
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引用次数: 3

Abstract

A chaotic detection scheme for a small-sized range-spread target in white Gaussian noise is developed. The basic idea is that a chaotic oscillator system is less influenced by noise, but it is very sensitive to periodic or pseudo-periodic signals. Firstly we concatenate the echoes with the same interested range cells from three successive pulses transmitted by high resolution radar end to end into a time series. The time series has certain pseudo-periodicity. Then the pseudo-periodic signal generated artificially is introduced into a Duffing oscillator system which is in the critical chaotic phase state. By adjusting the intensity of the noisy signal according to the estimated noise power, the false alarm ratio can be kept within an acceptable range. Then we determine the presence or absence of a target by judging the negative or positive maximal Lyapunove exponent of the Duffing equation. The Monte Carlo simulations for a small-sized range-spread target show that the proposed method significantly outperforms the traditional integrator detector and can improve about 2–5 dB in signal-to-noise ratio performance versus the integrator.
利用混沌Duffing振荡器检测小型距离扩展目标的研究
提出了一种高斯白噪声条件下小尺寸距离扩展目标的混沌检测方法。基本思想是混沌振荡器系统受噪声的影响较小,但对周期或伪周期信号非常敏感。首先,我们将高分辨率雷达端到端连续发射的三个脉冲中具有相同兴趣距离单元的回波串接成一个时间序列。时间序列具有一定的伪周期性。然后将人工产生的伪周期信号引入处于临界混沌相态的Duffing振荡器系统。根据估计的噪声功率调整噪声信号的强度,使虚警率保持在可接受的范围内。然后通过判断Duffing方程的最大Lyapunove指数的正或负来确定目标的存在与否。对小尺寸距离扩展目标的蒙特卡罗仿真表明,该方法明显优于传统的积分器检测器,比积分器的信噪比性能提高约2-5 dB。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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