混沌信号雷达原理

Abstract
The noise-like chaotic signal can be generated with very simple nonlinear circuit, has very broad bandwidth and good correlation properties. These characteristics have drawn considerable attentions in radar community. Much research has been devoted its applicability to radar. In the past, the chaotic signal serves only for a transmit signal and the traditional correlation-type receiver is used for processing. In this sense, the chaotic signal is acting as a radar waveform in the noise signal radar and hence its performance advantage is not distinct. Here we present a scheme for processing chaotic radar signal. We find a simple relation between the target parameters (range and velocity) and the system parameters of chaos-generating system. With this relation, the measurement of the target parameters is transformed into estimation of the system parameters from the radar return signals. Equipped with high-resolution parameter estimation techniques, the proposed principles provide a way to develop high-resolution noise signal radar. Keywords: Chaos synchronization, Parameter estimation, Noise signal radar, Chaotic signal radar.

C1 dv1 1 = (v2 − v1 ) − f (v1 ) dt பைடு நூலகம் dv 1 C2 2 = (v1 − v2 ) + i3 dt R di L 3 = −v2 − R0 i3 dt
(1)
where v1 and v2 are the voltage across the capacitors and i3 is the current in the inductor. R0 is the internal resistance of the inductor and f (v) is a piecewise-linear function
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Introduction
Chaos, generated by nonlinear dynamical circuits and systems, is a kind of deterministic phenomena, has broadband spectra and may vary significantly for small initial condition fluctuation. These characteristics afford chaos great potentials for various engineering applications. Inspired by the synchronization theory [1] of Pecora and Carroll, chaos-based information techniques [2] have acquired wide attention and great advances have been made for chaotic communications [3], [4]. In radar community, the deterministic and noise-like properties of chaos are also expected for applications. Current application strategies can be broadly classified into three categories. In the first category, it is found that some radar returns are chaotic rather than purely random and hence chaos theory can be used to process the conventional radar signals [5], [6]. The second one is to generate binary codes by chaos and implement
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Supported by Doctoral Training Program of The Ministry of Education, PRC, 20020288004
coded radar [7], [8]. The main purposes are to develop flexible codes having the desired randomness. In the third category, the chaos is utilized as a continuous random signal to implement noise signal radar (NSR) [9]-[12]. Current researches mainly include the generation and performance analyses of the chaotic signals [13]-[16]. Some prototype radar systems are also reported [12], [17]. It is demonstrated that the chaotic signal can be easily generated with simple nonlinear circuits and has very broad bandwidth and good correlation properties that offer great range resolution and unambiguity. Our research in this article is fallen into the third aspect with emphasis on signal processing. To be different, we will call this radar as chaotic signal radar (CSR). In the past study of the CSRs, the chaotic signal serves only for transmit signal and the traditional correlation-type receiver is used to process radar signals [12], [17], [18]. The deterministic property and controllability of chaotic signals are not exploited for processing applications and hence performance advantage of the CSRs is not distinct. In this paper, we present a processing scheme of chaotic radar signals by exploiting the generating mechanism of transmitted chaotic signals. We find a simple relation between the target parameters (range and velocity) and the system parameters of chaos-generating circuits. With this relation, the measurement of the target parameters is transformed into estimation of the circuit parameters. The advances in parameter estimation techniques [19]-[22] make the scheme be implementable in the measurement of range and velocity. The proposed scheme is not suitable for NSRs, because the generating models of the noise signals are generally not available.
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Chaotic signal and Its Time Scaling Version
The proposed scheme is based on a basic observation. Suppose that x(t ) is a chaotic signal generated by some chaotic circuit with a set of parameters { p} . Then the time-scaling signal x( st ) with scalar s can be shown to be generated by the same chaotic circuit with a new set of parameters { p′} . By exploiting the relationship between { p} and { p′} , we can determine the scalar s . This observation can be better explained by a chaotic circuit. Let us consider the well-known Chua’s circuit [23], as shown in Fig.1(a). The differential equation describing the circuit is given by