航空发动机约简遗传规划起动非线性动态模型

提出了一种新的用于航空发动机最优化起动过程数据驱动动态建模的约简遗传规划(PGP)算法。这种模型采用遗传规划产生航空发动机辨识模型的输入输出非线性模型集,并以二叉树结构表征函数项,运用正交最小二乘算法(OLS)估计二叉树分支对于模型精度的贡献并据此去除复杂、冗余的函数项,从而加快遗传规划的收敛速度,最后通过GP进化可获得简单、可靠、准确的线参数非线性线参数动态模型。实际发动机起动过程建模应用案例证明,这种思路对于具有非线性输入输出关系特征的数据可以产生鲁棒性好、解析性强的线参数非线性模型。      

一种基于观测站数目最小化的TDOA/FDOA无源定位算法

在三维（3D）运动目标无源定位系统中,无模糊定位最少需要4个观测站。而传统的两步加权最小二乘（TSWLS）及其改进的闭式算法至少需要5个观测站进行求解,当减少一个观测站时,这些闭式算法往往无法提供可靠解。针对这一问题,提出一种最小化观测站数目的到达时间差（TDOA）与到达频率差（FDOA）定位算法。该算法是一种闭式解法并且能够在三维场景下仅使用4个观测站进行定位。该算法分为两步：第1步分离传统的TSWLS算法中未知参数空间,建立了一组新的等式,并且利用加权最小二乘（WLS）算法得到目标位置与速度的初始值;第2步利用泰勒级数展开算法将中间变量线性化,对目标位置和速度初始值进一步校正。理论分析证明了在适当的噪声水平下该算法能够达到克拉美罗界（CRLB）。此外,计算机仿真表明仅使用4个观测站时,该算法对于近场以及远场目标参数的估计精度在测量噪声较小时可以实现CRLB;并且还表明使用5个观测站估计时,该算法比TSWLS及其改进算法能更好地适应大的测量噪声。     

Correlation-weighted least squares residual algorithm for RAIM

The Least Squares Residual (LSR) algorithm, one of the classical Receiver Autonomous Integrity Monitoring (RAIM) algorithms for Global Navigation Satellite System (GNSS), presents a high Missed Detection Risk (MDR) for a large-slope faulty satellite and a high False Alarm Risk (FAR) for a small-slope faulty satellite. From the theoretical analysis of the high MDR and FAR cause, the optimal slope is determined, and thereby the optimal test statistic for fault detection is conceived, which can minimize the FAR with the MDR not exceeding its allowable value. To construct a test statistic approximate to the optimal one, the Correlation-Weighted LSR (CW-LSR) algorithm is proposed. The CW-LSR test statistic remains the sum of pseudorange residual squares, but the square for the most potentially faulty satellite, judged by correlation analysis between the pseudorange residual and observation error, is weighted with an optimal-slope-based factor. It does not obey the same distribution but has the same non-central parameter with the optimal test statistic. The superior performance of the CW-LSR algorithm is verified via simulation, both reducing the FAR for a small-slope faulty satellite with the MDR not exceeding its allowable value and reducing the MDR for a large-slope faulty satellite at the expense of FAR addition.     

一种4站情况下基于TDOA/FDOA的无源定位方法

在基于时频差的三维运动目标无源定位系统中,针对在4个接收站的情况下搜索法实时性低的问题,提出了一种基于改进的加权最小二乘法（MWLS）与萤火虫算法（FA）相结合的无源定位方法（MWLS-FA）。该方法的第1步通过构造一组新的方程来对加权最小二乘（WLS）方法进行改进,使得改进后的WLS方法在4站情况下也能得到目标位置和速度的初始值,第2步利用这个初始值为FA方法提供一个动态的搜索区域,同时在约束条件的添加和参数选择两个方面针对性地对FA方法做出了调整和改进。仿真结果表明,该方法在4站情况下对目标的定位精度可以达到克拉美罗下限（CRLB）,而且在实时性和抗噪性方面优于传统的搜索法,同时该方法在5站情况下的抗噪性能优于两步加权最小二乘法（TSWLS）和约束加权最小二乘（CWLS）法。     

双机协同无源定位算法

相较于有源定位,只能利用到达角(Angle of Arrival,AOA)的双机协同无源定位对目标的观测维度很低,这会导致对目标的定位精度低或迭代收敛速度慢等问题发生。对此,利用有限的测量值研究更优秀的算法以提高定位精度具有实际意义。首先,介绍了普通最小二乘法、加权最小二乘法、总体最小二乘法 3种基于最小二乘算法的定位算法;然后,介绍了高斯-牛顿迭代法(Gauss-Newton iteration method,GNIM)和加权工具变量伪线性估计法 (Weighted Instrumental Variable Pseudolinear Estimation Method,WIVPLE)2种基于最大似然估计的定位算法;最后,使用蒙特卡洛法在不同误差条件和几何构型下对这些算法的定位精度进行仿真实验。     

回溯降维相干分布式非圆信号DOA快速估计

在相干分布式非圆(CDNC)信号波达方向(DOA)估计中,针对阵列输出矩阵扩展后维数增加带来的较大运算量问题,基于降维的多级维纳滤波(MSWF)技术,引入回溯优化思想,提出了一种快速估计算法。该算法首先利用信号非圆特性扩展阵列输出矩阵,然后通过MSWF递推分解快速求出信号子空间,避免了计算阵列协方差矩阵及特征分解,并且在递推过程中引入回溯优化机制提高了各级匹配滤波器的估计性能,最后由最小二乘(LS)或者总体最小二乘(TLS)得到DOA估计。仿真分析表明,所提算法与相干分布式非圆信号旋转不变子空间算法(CDNC-ESPRIT)性能相当,但复杂度得到了大幅度降低,相比于基于MSWF的非圆信号快速子空间(NC-MSWF-FS)算法,在较小的复杂度代价下大幅度提升了低信噪比时的估计性能,并且对初始参考信号的选取具有了较强的鲁棒性。     

传感器参数误差下的运动目标TDOA/FDOA无源定位算法

在运动目标无源定位系统中，许多算法的前提是精确已知传感器的位置以及速度，但实际情况下可利用的传感器的参数均会存在一些噪声扰动。针对这一问题，提出一种改进的两步加权最小二乘（TSWLS）时差（TDOA）与频差（FDOA）定位算法。该算法是一种闭式算法并且分为2步。第1步与经典的两步加权最小二乘算法相同，第2步进一步研究了额外变量与目标参数之间的关系并且建立了新的矩阵方程。随后，利用加权最小二乘技术给出了最终解。理论分析证明了在测量噪声较小时该算法能够达到克拉美罗界（CRLB）。所提算法具有计算复杂度低，实时性高的优点；另外，经过适当的维度调整，该算法同样适用于对多非相交源进行定位求解。计算机仿真进一步证明了理论分析的正确性。     

An enhanced least squares residual RAIM algorithm based on optimal decentralized factor

The Least Squares Residual (LSR) algorithm is commonly used in the Receiver Autonomous Integrity Monitoring (RAIM). However, LSR algorithm presents high Missed Detection Risk (MDR) caused by a large-slope faulty satellite and high False Alert Risk (FAR) caused by a small-slope faulty satellite. In this paper, the LSR algorithm is improved to reduce the MDR for a large-slope faulty satellite and the FAR for a small-slope faulty satellite. Based on the analysis of the vertical critical slope, the optimal decentralized factor is defined and the optimal test statistic is conceived, which can minimize the FAR with the premise that the MDR does not exceed its allowable value of all three directions. To construct a new test statistic approximating to the optimal test statistic, the Optimal Decentralized Factor weighted LSR (ODF-LSR) algorithm is proposed. The new test statistic maintains the sum of pseudo-range residual squares, but the specific pseudo-range residual is weighted with a parameter related to the optimal decentralized factor. The new test statistic has the same decentralized parameter with the optimal test statistic when single faulty satellite exists, and the difference between the expectation of the new test statistic and the optimal test statistic is the minimum when no faulty satellite exists. The performance of the ODF-LSR algorithm is demonstrated by simulation experiments.     

航空发动机部件特性修正技术研究

针对传统部件特性修正方法未考虑发动机多状态导致修正精度不高的问题,提出了1种基于粒子群优化和滑动最小二乘法的某型发动机部件特性修正方法。该方法利用粒子群优化算法分别求得在发动机不同状态下的修正系数,并以这些系数为基础,采用滑动最小二乘方法拟合修正系数曲面,从系数曲面上获取原有部件特性图上各点对应的修正系数,从而得到修正特性。试验结果表明:该方法克服了传统方法的不足,提高了特性修正精度,为开展单机监控和视情维修提供准确的部件数据基础。     

Real-time mosaicking for infrared videos from an oblique sweeping camera

Image mosaicking is widely used in Geographic Information Systems (GISs) for large-scale ground surface analysis. However, most existing mosaicking methods can only be used in offline processing due to the enormous amounts of computation. In this paper, we propose a novel and practical algorithm for real-time infrared video mosaicking. To achieve this, a novel fast template matching algorithm based on Sum of Cosine Differences (SCD) is proposed to coarsely match the sequential images. The high speed of the proposed template matching algorithm is obtained by computing correlation with Fast Fourier Transform (FFT). We also propose a novel fast Least Squares Matching (LSM) algorithm for inter-frame fine registration, which can significantly reduce the computation without degrading the matching accuracy. In addition, the proposed fast LSM can effectively adapt for noise degradation and geometric distortion. Based on the proposed fast template matching algorithm and fine registration algorithm, we develop a practical real-time mosaicking approach which can produce seamless mosaic image highly efficiently. Experiments on synthetic and real-world datasets demonstrate that the proposed algorithm is not just computationally efficient but also robust against various noise distortions.     

基于约简遗传规划的线参数模型及在航空发动机起动建模中的应用

提出了一种新的约简遗传规划(PGP)算法和一种新的基于约简遗传规划的航空发动机起动动态线参数模型.这种模型采用遗传规划产生航空发动机起动模型的输入输出非线性模型集,并以二叉树结构表征函数项,运用正交最小二乘算法(OLS)估计二叉树分支(基本函数项)对于模型精度的贡献并去除复杂、冗余的函数项,从而加快遗传规划的收敛速度,最后通过GP进化可获得简单、可靠、准确的线参数非线性模型.发动机起动过程试车数据建模和与支持向量机的比较证明,这种方法可以产生适用性好、解析性强的线参数非线性模型,产生的模型可获得与支持向量机相当甚至更优的结果.     

基于均匀圆阵的信号二维方向角高精度估计

基于均匀圆阵(UCA),提出一种信号二维方向角的高精度估计方法。首先,充分利用了信号的空、时域信息,构造时空旋转矩阵,从而达到多个信源分离的目的。其次,直接利用UCA的阵列流形,采用最小二乘法估计信号二维方向角。最后,给出解相位整周期性模糊的方法。计算机仿真表明了此方法具有估计精度高,对阵元的幅相误差鲁棒性强等特点。     

基于LS-SVM的飞控系统传感器故障诊断

针对飞控系统故障诊断难的问题,利用最小二乘支持向量机(LS-SVM)设计了一个飞控系统传感器的故障诊断系统.仿真试验结果表明,LS-SVM具有很高的建模精度和较强的泛化能力,基于LS-SVM的故障诊断系统能对各型传感器的故障进行诊断和定位,验证了该方法的有效性和先进性.     

求解线性矛盾方程组的递推Householder变换法

 求解线性矛盾方程组是工程实践中经常遇到的问题。目前主要采用法方程组解法和基于各种正交变换的三角化解法。由于法方程组系数矩阵的病态条件数是原矛盾方程组系数矩阵病态条件数的平方,所以计算精度较差,有时甚至得到完全错误的结果。因此一些计算精度要求高的问题和高阶方程组的求解,多采用三角化法。但是,三角化法只能进行一次性处理,尚未出现随数据更新的实时递推算法。许多需要在线处理和数据存储最大的问题,只好采用一般递推最小二乘法。     

模糊最小二乘系统辨识——用于等精度测量

提出了一种新的系统辨识的方法--模糊最小二乘系统辨识法。它适用于处理等精度条件下测量得到的数据;同时,给出了一种确定测量数组中各次测量数据隶属度的方法,并进行了应用举例,所得结果与传统辨识方法结果比较,证明此法对提高系统辨识精度效果显著。     

Unstable unsteady aerodynamic modeling based on least squares support vector machines with general excitation

Common, unsteady aerodynamic modeling methods usually use wind tunnel test data from forced vibration tests to predict stable hysteresis loop. However, these methods ignore the initial unstable process of entering the hysteresis loop that exists in the actual maneuvering process of the aircraft. Here, an excitation input suitable for nonlinear system identification is introduced to model unsteady aerodynamic forces with any motion in the amplitude and frequency ranges based on the Least Squares Support Vector Machines (LS-SVMs). In the selection of the input form, avoiding the use of reduced frequency as a parameter makes the model more universal. After model training is completed, the method is applied to predict the lift coefficient, drag coefficient and pitching moment coefficient of the RAE2822 airfoil, in sine and sweep motions under the conditions of plunging and pitching at Mach number 0.8. The predicted results of the initial unstable process and the final stable process are in close agreement with the Computational Fluid Dynamics (CFD) data, demonstrating the feasibility of the model for nonlinear unsteady aerodynamics modeling and the effectiveness of the input design approach.     

非理想均匀圆阵的波达方向和多普勒频率联合估计

针对均匀圆阵存在一般阵列误差 (如阵元的幅相误差和安装位置误差等 )的情况 ,提出了多个信号的波达方向和多普勒频率估计方法。直接利用均匀圆阵的阵列流形 ,采用波达矩阵法估计各个信号的多普勒频率。由一般阵列误差的统计特性构造加权矩阵 ,采用加权总体最小二乘法估计各个信号的波达方向。此方法具有鲁棒性强等特点。计算机仿真证明了此方法的有效性     

星基ADS与雷达误差校准算法的研究

基于星基自动相关监视(ADS)系统和雷达各自的特点,分析了空中交通管制中ADS与雷达数据融合的模型,提出了在传统的地心地固(ECEF)坐标系中星基ADS和雷达系统误差校准的算法。同时,针对ADS数据的特性,又进一步提出了在Geodetic坐标系和以雷达站为极点的极坐标系(以下简称雷达站极坐标系)中的系统误差校准算法。最后,对校准效果进行了仿真分析和比较,并介绍了一种有效应用上述算法的方法。     

Residual stress analysis of multi-pass cold spinning process

Uncontrolled residual stresses have significant effects on the service time and defects of the spun parts. Nowadays, X-Ray Diffraction(XRD) method has been widely used in the residual stress measurement of industry products with different forming processes. The calculated residual stress is usually obtained from the data fitting slope of strain and angle with Ordinary Least Squares(OLS) method. But this fitting method is not always suitable for the big fluctuant data. In this paper, the Weighted...     

大型客机目录价格预测研究

大型客机作为一种昂贵的商品,其价格是非常重要的信息,定价合理与否直接关系到市场前景和商业成功。目录价格是大型客机售价的基础,直接影响客户购买意愿以及后续合同谈判。以波音公司和空客公司的主力干线飞机为样本,基于最小二乘回归法(Ordinary Least Squares Regression,OLSR)建立了大型客机目录价格预测模型,模型对价格的解释能力好,预测误差小,为大型客机的目录价格制定提供了相关的理论依据。