摘要: In previous work, we proposed to generate random samples using chaotic maps. More specifically, we demonstrated that Gaussian samples can be obtained via two random number generators that utilize first order or second order chaoti... 展开 In previous work, we proposed to generate random samples using chaotic maps. More specifically, we demonstrated that Gaussian samples can be obtained via two random number generators that utilize first order or second order chaotic maps. In this paper we extend this work and propose to utilize the chaos-based random generators to develop a Gaussian FM signal that can be exploited for radar imaging. For this purpose, we fine-tune the chaotic map parameters of the Gaussian FM signal until we obtain a white wide-band spectrum, which is computed as an ensemble average, and analyze the corresponding ambiguity surface of the signal. We observe that the ensemble average of the ambiguity surface approaches an ideal two dimensional delta with uniformly distributed sidelobes on the range-Doppler plane. On average the sidelobes of the surface have intensity inversely proportional to the length of the processed echo. For completeness, we compare the variance of the Gaussian FM ambiguity function to that of a random binary phase code with comparable bandwidth. Furthermore, we show through simulations that Fourier processing of the Gaussian FM signal can yield a high-resolution range-Doppler image aircraft with prominent point scattering points over a substantial SNR dynamic range. 收起