An algorithm of digital watermarking based on hyperchaos sequence and the discrete fractional Fourier transform (DFRFT) is proposed. First, the watermark image is scrambled in the spatial domain. The original image and the watermark image are discrete fractional Fourier transformed respectively with different order. Secondly, the watermark image's real part and imaginary part are encrypted by the cipher sequence, which is generated by the hyperchaos sequence. Thirdly, the secondary visual important part of the original image is chosen for embedding into the watermark. At last, the watermark image is obtained after Fourier inversely transformed. The robustness of the watermark image under different attacks such as noise, JPEG compression, the cropping and gaussian low-pass filter is analyzed and the results demonstrate that the embedding scheme has good performance of robustness.

Modern radar systems should transmit different waveforms according to different environment. So how the transmitted waveform adapts in response to information regarding the radar environment is an important problem in radar waveform design. In this paper, based on mutual information and water-filling method, a novel adaptive waveform design method is used to obtain optimized waterfilling waveform when there is no clutter. In simulation, extended target with Gaussian random process is considered. Simulation results show that the optimized transmitted signal allocates as more energy into different modes of target response as possible and the optimal radar waveform will spread its energy among most of the spectral peaks of the target response. Finally, the whole paper is summarized.

Cognitive radar is an intelligent system, and it can adaptively transmit waveforms to the complex environment. The intelligent radar system should be able to provide different trade-offs among a variety of performance objectives. In this paper, we investigate the mutual information (MI) in signal-dependent interference and channel noise. We propose a waveform design method which can efficiently synthesize waveforms and provide a trade-off between estimation performance and detection performance. After obtaining a local optimal waveform, we apply the technique of generating a constant modulus signal with the given Fourier transform magnitude to the waveform. Finally we obtain a waveform that has constant modulus property.