LDPC码低复杂度译码算法研究

在描述置信传播（BP）译码算法基础上，研究和分析了两种降低复杂度的译码算法。Min-Sum算法主要讨论了简化校验节点的消息更新运算，并应用密度进化方法对此算法进行极限性能分析，求出最佳修正参数α以改进译码性能。强制收敛技术致力于减少BP和MSA算法译码过程中“激活”节点的数目，从而降低译码复杂度。AWGN信道仿真结果表明，两种算法在降低译码复杂度的同时，译码性能没有明显降低。     

某型蒸发式稳定器气动及燃烧特性研究

为解决亚燃冲压发动机在高速低温来流条件下的可靠点火、火焰稳定和高效燃烧问题,对某型蒸发式火焰稳定器分别进行了冷态流场和燃烧流场的数值研究,并与常规V型火焰稳定器进行了对比分析。研究结果表明:在给定范围内,蒸发式稳定器随来流速度的增大,总压恢复系数和停留时间明显减小,回流区长度、回流率和燃烧效率变化不大;与相同槽宽的常规V型火焰稳定器相比,回流率明显减小,总压恢复系数、回流区长度和停留时间略有减小。蒸发式稳定器后部形成明显的回流区,且基本上不受外部主流流动的干扰,通过单独控制稳定器局部供油,可以使稳定器在最佳油气比下工作,有利于在高速来流条件下可靠工作。     

《火箭推进》征稿启事

一、《火箭推进》是航天推进技术研究院主办的运载器与导弹动力专业学术刊物,专业方向侧重于火箭发动机。二、《火箭推进》为双月刊,国内外公开发行,刊载火箭发动机、吸气式发动机、非常规动     

自适应天线抗干扰性能研究

分析了适用于雷达抗干扰的一些自适应天线波束形成算法,将子空间正交投影算法应用于雷达抗干扰,针对子空间分解过程中特征向量不能完全正交的问题,采用约束化子空间分解算法,来保证子空间特征向量的正交性.最后通过仿真证明:子空间跟踪算法相对于传统的一些自适应算法具有更强的抗干扰性能.     

星载SAR在轨成像实时处理算法研究

星载合成孔径雷达(SAR)分辨率和幅宽的不断提高,其产生的原始数据率越来越大,采用在轨实时成像处理形成图像,在图像域再进行传统的图像数据处理和传输,有助于降低星-地数据传输速率,为了提高星载SAR在轨成像处理的实时性,文章分析了星上特殊条件对星载SAR处理算法实时性所提出的约束,对RD、波束域、CS等经典的星载SAR成像处理算法的运算量进行了比较,以CS算法为例,研究了相位补偿因子对CS成像处理算法的实时性影响,提出了一种补偿因子区域不变的CS成像算法,它极大地减少了成像处理算法的运算量,并通过仿真实验结果验证了该算法的有效性。     

一种大面积比喷管的分段式设计与数值分析

为了满足大推力上面级发动机大面积比喷管的设计需求,采用了排放冷却前段和单壁辐射冷却尾段的分段式设计方案。在排放冷却前段传热计算的基础上,通过对内流场进行数值模拟,重点研究了单壁尾段在引入上游排放冷却气氢情况下的冷却特性和喷管效率。结果表明:对于大面积比喷管,采用带二次流的单壁金属喷管延伸段是现实可行的,有望达到较好的冷却保护效果并提高喷管效率。     

A strategic flight conflict avoidance approach based on a memetic algorithm

Conflict avoidance （CA） plays a crucial role in guaranteeing the airspace safety. The cur- rent approaches, mostly focusing on a short-term situation which eliminates conflicts via local adjust- ment, cannot provide a global solution. Recently, long-term conflict avoidance approaches, which are proposed to provide solutions via strategically planning traffic flow from a global view, have attracted more attentions. With consideration of the situation in China, there are thousands of flights per day and the air route network is large and complex, which makes the long-term problem to be a large-scale combinatorial optimization problem with complex constraints. To minimize the risk of premature convergence being faced by current approaches and obtain higher quality solutions, in this work, we present an effective strategic framework based on a memetic algorithm （MA）, which can markedly improve search capability via a combination of population-based global search and local improve- ments made by individuals. In addition, a specially designed local search operator and an adaptive local search frequency strategy are proposed to improve the solution quality. Furthermore, a fast genetic algorithm （GA） is presented as the global optimization method. Empirical studies using real traffic data of the Chinese air route network and daily flight plans show that our approach outper- formed the existing approaches including the GA .based approach and the cooperative coevolution based approach as well as some well-known memetic algorithm based approaches.     

A salient edges detection algorithm of multi-sensor images and its rapid calculation based on PFCM kernel clustering

Multi-sensor image matching based on salient edges has broad prospect in applications, but it is difficult to extract salient edges of real multi-sensor images with noises fast and accurately by using common algorithms. According to the analysis of the features of salient edges, a novel salient edges detection algorithm and its rapid calculation are proposed based on possibility fuzzy C-means （PFCM） kernel clustering using two-dimensional vectors composed of the values of gray and texture. PFCM clustering can overcome the shortcomings that fuzzy C-means （FCM） cluster- ing is sensitive to noises and possibility C-means （PCM） clustering tends to find identical clusters. On this basis, a method is proposed to improve real-time performance by compressing data sets based on the idea of data reduction in the field of mathematical analysis. In addition, the idea that kernel-space is linearly separable is used to enhance robustness further. Experimental results show that this method extracts salient edges for real multi-sensor images with noises more accurately than the algorithm based on force fields and the FCM algorithm; and the proposed method is on average about 56 times faster than the PFCM algorithm in real time and has better robustness.     

A practical nonlinear robust control approach of electro-hydraulic load simulator

This paper studies a nonlinear robust control algorithm of the electro-hydraulic load simulator （EHLS）. The tracking performance of the EHLS is mainly limited by the actuator＇s motion disturbance, flow nonlinearity, and friction, etc. The developed controller is developed based on the nonlinear motion loading model. The problems of the actuator＇s disturbance and flow nonlinearity are considered. To address the friction problem, the friction model of the loading motor is identified experimentally. The friction disturbance is compensated using the obtained friction model. Therefore, this paper considers the main three factors comprehensively. The developed algorithm is easy to apply since the controller can be obtained just with one step back-stepping design. The stability of the developed algorithm is proven via Lyapunov analysis. Both co-simulation and experiments are performed to verify the effectiveness of this method.