Through the analysis of common moving target detecting algorithms, this paper proposes a moving target detecting algorithm based on S usan edge detection and frame difference. It detects the edge information of current frame image by Susan operator, then taking a differential operation between the current frame and the next frame image to get the outline of moving target. Finally, it extracts the target by using an and operation with two parts of information. The experimental results show that this algorithm is simple and effective, making up for the deficiency of a single frame difference method.

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In this paper, a hyperbolic tangent variable step-size convex combination of the least mean square (HTVSCLMS) algorithm is proposed and analyzed. The compromise between the convergence speed and the steady-state error for two filters in a convex combination of the least mean square (CLMS) algorithm is avoided by this study. In the proposed algorithm, the big step-size filter is replaced by a filter whose iteration step-size is a modified function based on hyperbolic tangent function. Thus, hyperbolic tangent nonlinear relationship between step-size and error is constructed. Simultaneously, the small step-size filter remains unchanged but fixed. Therefore, the slow convergence speed and the weak anti-interference ability of fixed step-size CLMS were conquered. Simulation results show that the HTVSCLMS algorithm, compared with CLMS algorithm and variable step-size CLMS (VSCLMS) algorithm, not only has superior capability of tracking in the presence of noise and in a stable and even non-stable environment but also can maintain a better convergence. KeywordsLeast mean square (LMS) filters, convex combination, variable step-size, hyperbolic tangent function

An advanced runway tracking model for landing of Unmanned Aerial Vehicle (UAV) based on vision is proposed. This model builds on existing work, but extends it to achieve efficiency, robustness, and address some critical situations such as instant sun glare, instant heave fog, cloud hold back, and instant extinction of approaching marking, and so on. These situations always have bad effects to our visual landing system of UAV. So, two different schemes containing several approaches constitute the core of our visual system to address these situations. We use Zernike moments as a regionbased shape descriptor of runway and save the changing pattern through landing process of pretest. At the real flight time, we use particle filter to track the change of the Zernike moments that calculated on each potential region of runway at each frame. When this change is too big, exceed the threshold, we use the pretest data to reconstruct the shape of the runway. The performance of the presented schemes has been assessed throuth processing several video sequences that captured by the real landing plane. The experiment shows, this tracking model is more efficient and robust and can be used on a vision sensor for landing equipment of UAV or for an aerial vehicle's aided system.

At present, methods of bit error rate (BER) analysis for frequency-hopping (FH) system can only solve the problem of barrage jamming, but these are no comprehensive means to follower jamming (FJ). This paper proposes a method of BER analysis with FJ based on frequency hopping M-ary frequency-shift keying (FH/MFSK) system. Through the analysis of the mechanism of FH/MFSK system, assuming the wireless channel is an AWGN channel, the BER formulas for different jamming types are derived, respectively, from the point of one-dimensional probability density function of the output signal of the envelope detector, while judgment principle of envelope detecting method is used. Results show that the BER of multiple FH/MFSK system with FJ is relatively lower. In the worst case of FJ, the BER of FH/4FSK system and FH/8FSK system is reduced by 2 dB and 3 dB, respectively, compared with that of FH/2FSK system. The method of BER analysis proposed provides an effective means to research the BER with FJ in depth.