充分统计量在数字信号处理中的应用研究

分析了充分统计量在数字信号处理中的应用,简述了充分统计量的理论模型,重点研究了充分统计量在高斯信道中的应用,结合具体的实例对传统意义下的基于贝叶斯准则的估计和基于充分统计量的估计的性能进行了比较分析;分析比较了基于充分统计量的估计与传统的基于线性模型估计的一致性,全文以具体简洁的实例,针对充分统计量理论用于信号数字参数的估计问题提供了参考。     

自抗扰技术在船载天线伺服系统中的应用研究

为减小船摇扰动对船载天线伺服系统指向及跟踪精度的影响，引入线性自抗扰控制器（LADRC）对伺服系统位置环进行改进。首先对天线伺服系统模型进行简要分析，建立系统状态空间方程；然后利用LADRC对系统进行改进，并对其参数设计进行了详细介绍，同时为提高系统动态跟踪性能，利用TD微分器提取目标速度信息进行前馈补偿；最后经实验测试验证，LADRC相对于传统PID控制器能够保持天线伺服系统动态性能不下降，同时有效提高系统的抗船摇性能。     

Real-time fault detection method based on belief rule base for aircraft navigation system

Real-time and accurate fault detection is essential to enhance the aircraft navigation system’s reliability and safety. The existent detection methods based on analytical model draws back at simultaneously detecting gradual and sudden faults. On account of this reason, we propose an online detection solution based on non-analytical model. In this article, the navigation system fault detection model is established based on belief rule base (BRB), where the system measuring residual and its changing rate are used as the inputs of BRB model and the fault detection function as the output. To overcome the drawbacks of current parameter optimization algorithms for BRB and achieve online update, a parameter recursive estimation algorithm is presented for online BRB detection model based on expectation maximization (EM) algorithm. Furthermore, the proposed method is verified by navigation experiment. Experimental results show that the proposed method is able to effectively realize online parameter evaluation in navigation system fault detection model. The output of the detection model can track the fault state very well, and the faults can be diagnosed in real time and accurately. In addition, the detection ability, especially in the probability of false detection, is superior to offline optimization method, and thus the system reliability has great improvement.     

Optimization on conventional and electric air-cycle refrigeration systems of aircraft: A short-cut method and analysis

The air-cycle refrigeration system is widely used in commercial and military aircraft, and its efficiency greatly affects aircraft performance. Nowadays, this system requires a more efficient design and optimization method. In this paper, a short-cut optimization method with high efficiency and effectiveness is introduced for both conventional and electric air-cycle refrigeration systems. Based on the system characteristics, a four-layer parameter matching algorithm is designed which avoids computational difficulty caused by simultaneous equations. Fuel penalty is chosen as the objective function of optimization; design variables are reduced based on sensitivity analysis to improve optimization efficiency. The results show that the 3-variable optimization of the conventional air-cycle refrigeration system can obtain almost the same results as the traditional 6-variable optimization in that these two optimizations can both significantly reduce the fuel penalty. However, the computer running time of the 3-variable optimization is much shorter than that of the 6-variable optimization. The optimal fuel penalty of the electric air-cycle refrigeration system is lower than that of the conventional one. This study can provide reference for optimizing the air-cycle refrigeration system of aircraft.     

A novel none once per revolution blade tip timing based blade vibration parameters identification method

The vibration caused blade High Cycle Fatigue (HCF) is seriously affects the safety operation of turbomachinery especially for aero-engine. Thus, it is crucial important to identify the blade vibration parameters and then evaluate the dynamic stress amplitude. Blade Tip Timing (BTT) method is one of the promising method to solve these problems. While, it need a high resolution Once Per Revolution (OPR) signal which is difficult to get for the aero-engine. Here, a Coupled Vibration Analysis (CVA) method for identifying blade vibration parameters by a none OPR BTT is proposed. The method assumes that every real blade has its own vibration performance at a given speed. Whereby, it can take any blade as the reference blade, and the other blades using the reference blade as the OPR for vibration displacement calculating and further parameter identifying. The proposed method is validated by numerical model. Also, experimental studies are carried out on a straight blade and a twisted three dimensional blade test rig as well as a large industrial axial compressor respectively. The results show that the proposed method can accurately identify the blade synchronous vibration parameters and quantitatively evaluate the mistuning in bladed disks, which lays a foundation for the reliability improvement of aero-engine.     

A novel signal processing approach for LEO space debris based on a fence-type space surveillance radar system

The increase in space debris can seriously threaten regular activities in the Low Earth Orbit (LEO) environment. Therefore, it is necessary to develop robust, efficient and reliable techniques to understand the potential motions of the LEO debris. In this paper, we propose a novel signal processing approach to detect and estimate the motions of LEO space debris that is based on a fence-type space surveillance radar system. Because of the sparse distribution of the orbiting debris through the fence in our observations, we formulate the signal detection and the motion parameter estimation as a sparse signal reconstruction problem with respect to an over-complete dictionary. Moreover, we propose a new scheme to reduce the size of the original over-complete dictionary without the loss of the important information. This new scheme is based on a careful analysis of the relations between the acceleration and the directions of arrival for the corresponding LEO space debris. Our simulation results show that the proposed approach can achieve extremely good performance in terms of the accuracy for detection and estimation. Furthermore, our simulation results demonstrate the robustness of the approach in scenarios with a low Signal-to-Noise Ratio (SNR) and the super-resolution properties. We hope our signal processing approach can stimulate further work on monitoring LEO space debris.     

A novel LAAS pseudo-range error over-bound method based on improved pseudo-range error distribution model

The high level of safety demand of civil aviation requests local area augmentation system (LAAS) extremely high navigation integrity performance. A new LAAS pseudo-range error overbound method is proposed in this paper to improve the integrity of LAAS. Firstly, a more practical pseudo-range error distribution model is established. Then, by calculating the relationship between the statistical uncertainty of the model parameter and the integrity risk, a new method is proposed to calculate the pseudo-range error over-bound model. This method can effectively reduce the inflation factor and the resulting conservativeness of the over-bound model. Comparative experiments show that the method proposed in this paper performs better and satisfies the requirements of real applications.     

一种实现飞行品质参数实时辨识的实用方法

考虑到辨识算法收敛的可靠性及结果的精度，采用递推最小二乘估计、飞机运动模态连续－离散模型相互转换及递推极大似然估计，实现飞行品质参数的实时辨识。这种方法的优点在于算法的吸收域是全平面的。初值不影响算法的收敛性，能很好地满足实时性要求，同时还保证了结果精度。利用该方法对某型飞机铁鸟台实测数据进行了处理，取得了满意的结果。     

参数估计的样条函数法应用

简要了介绍了样条函数法的基本原理，飞机的数学模型和空气动力系数的样条函数表达式。用一算例说明了估计过程，获得了纵向气动导数随迎角变化的估计结果。同时还研究了迎角节点间隔和样条函数的次数对估计结果的影响，估计结果表明，样条函数法是非线性参数估计的重要方法之一，适当减小节点和间隔和适当增加样条函数次数可以提高参数估计的精度。