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A real-time detection algorithm for small space targets was presented based on FPGA and DSP, and the corresponding hardware was designed. With this system, the Video image, whose frame frequency reaches 40 Hz and the size reaches 512×512 pixels, could be processed in real-time application. Firstly, Max-Median filter was realized in FPGA to depress noise to solve the problem of mass computation and high speed request in image pre-processing. The segmentation of the moving target was done with an improved dual image difference and background suppression to ensure that small moving targets were detected in a low SNR and complex background image. And the algorithm could ensure diminishing false-alarm rate and maintaining detection probability. Practical application approved that the system perfectly meets the requirements of the real-time dim target detection and recognition in deep space.

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Active noise control (ANC) over an extended spatial region using multiple microphones and multiple loudspeakers has become an important problem. The maximum noise reduction (NR) potential over the control area is a critical evaluation variable as it indicates the fundamental limitation of a given ANC system. In this paper, a method to mathematically formulate the NR potential for any given multichannel ANC systems is developed. First, the residual error in the multichannel feedforward ANC system is formulated, and then the multiple-input-multiple-output problem is decomposed into the parallel-channel problem. The total energy of the residual error is further decomposed into three different terms representing (i) the signal coherence between the reference signals and error signals, (ii) the filter, and (iii) the system null space. The experimental results validate the proposed evaluation method and illustrate the effectiveness on the maximum NR performance evaluation for given systems. Using the proposed analyzing method, more insight into the contribution of each component to the NR potential can be achieved.

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