简化七阶CQKF及其在SINS大失准角初始对准中的应用

针对捷联惯性导航系统（SINS）大失准角初始对准的滤波过程，提出简化七阶正交容积卡尔曼滤波算法（7th-SCQKF）。根据简化容积卡尔曼滤波(CKF)理论，推导出改进的简化七阶CKF算法（7th-MSSRCKF），改进了原简化七阶CKF（7th-SSRCKF）的性能；同时，在7th-SSRCKF和7th-MSSRCKF基础上，引入正交半径准则，提出简化七阶CQKF（7th-SCQKF）算法，提高了滤波精度；并将简化七阶CQKF（7th-SCQKF）算法应用到SINS的大失准角初始对准仿真中，结果表明，7th-SCQKF比7th-MSSRCKF的滤波精度高，验证了新算法的正确性和有效性。     

A direct position determination method with combined TDOA and FDOA based on particle filter

The localization of a stationary transmitter using moving receivers is considered. The original Direct Position Determination (DPD) methods, with combined Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA), do not perform well under low Signal-to-Noise Ratio (SNR), and worse still, the computation cost is difficult to accept when the computational capabilities are limited. To get better positioning performance, we present a new DPD algorithm that proves to be more computationally efficient and more precise for weak signals than the conventional approach. The algorithm partitions the signal received with the same receiver into multiple non-overlapping short-time signal segments, and then uses the TDOA, the FDOA and the coherency among the short-time signals to locate the target. The fast maximum likelihood estimation, one iterative method based on particle filter, is designed to solve the problem of high computation load. A secondary but important result is a derivation of closed-form expressions of the Cramer-Rao Lower Bound (CRLB). The simulation results show that the algorithm proposed in this paper outperforms the traditional DPD algorithms with more accurate results and higher computational efficiency, and especially at low SNR, it is more close to the CRLB.     

Kalman filter based estimation of differential hardware biases with triangular interpolation technique for IRNSS

Ionosphere delay correction is the main error correction to the computation of single frequency user position using satellite navigation. However ionosphere delay consists of not only delay but also frequency dependent differential hardware biases from satellite and receiver ends. For ionosphere point of view, Indian Regional Navigation Satellite System (IRNSS) service area comes in equatorial anomaly region. It is a unique satellite navigation system which operates at L5 and S frequencies and consists of Geostationary Earth Orbit (GEO) and Geo Synchronous Orbit (GSO) satellite constellation. With IRNSS measurements availability, there is a good opportunity to estimate and analyse differential hardware biases with GEO/GSO combination and with equatorial ionosphere variation. In this paper, Kalman filter based estimation with triangular interpolation technique is used to estimate differential hardware biases for all IRNSS satellites and reference receivers at L5 frequency. The standard deviation of the 15?days of daily estimation of satellite differential hardware biases is in the range of 0.32 to 1.17 TECU for all IRNSS satellites. Similarly, the standard deviation of the 15?days of daily estimation varies up to 2.85 and 6.0 TECU for receiver differential hardware biases during calm and stormy period respectively. The ionosphere delay computed using estimated differential hardware biases is compared with Global Ionosphere Map (GIM) data. A rigorous analysis is carried out to study the error in the estimation in terms of input data noise level, satellite constellation and effect of latitude. Our result reveals that over IRNSS service area, there is an exponential increase in the error in the estimation of receiver differential hardware biases with respect to latitude.     

IIR滤波器在芯片原子钟中的应用

芯片原子钟是具有小体积,低功耗特点的原子钟。本文采用了IIR滤波器方案对芯片原子钟物理系统输出信号进行处理,该方案有利于减小芯片原子钟的体积、提高芯片原子钟短期频率稳定度。实验结果表明,与FIR滤波方案相比,IIR滤波器使用的FPGA资源减小了约58%;与现有模拟滤波方案相比,使用IIR滤波器方案的芯片原子钟频率稳定度提高了1.4×10~(-10)τ~(-1/2)(τ=1s-100s),电路面积减小了10%。     

Multi-input multi-output random vibration control using Tikhonov filter

Noises always disturb the control effect of an environment test especially in multi-input multi-output (MIMO) systems. If the frequency response function matrices are ill-conditioned, the noises in the driving forces will be amplified and the response spectral lines may awfully exceed their tolerances. Most of the major biases between the response spectra and the reference spectra are pro-duced by the amplified noises. However, ordinary control algorithms can hardly reduce the level of noises. The influences of the noises on both the auto-and cross-power spectra are analyzed in this paper. As a conventional frequency domain method on the inverse problem, the Tikhonov filter is adopted in the environment test to suppress the exceeding spectral lines. By altering regularization parameters gradually, the auto-power spectra can be improved in a closed control loop. Instead of using the traditional way of selecting regularization parameters, we observe the coherence change to estimate noise eliminations. Incidentally, the requirement of coherence control can be realized. The errors of the phase are then studied and a phase control algorithm is introduced at the end as a sup-plement of cross-power spectra control. The Tikhonov filter and the proposed phase control algo-rithm are tested numerically and experimentally. The results show that the noises in the vicinity of lightly damped resonant peaks are more stubborn. The response spectra are able to be greatly improved by the combination of these two methods.     

The Western Crete geodetic infrastructure: Long-range power-law correlations in GPS time series using Detrended Fluctuation Analysis

The Global Positioning System makes it possible, nowadays, to measure crustal displacements with unprecedented accuracy. These measurements can improve our understanding of the spatio-temporal evolution of motion along tectonic plate boundaries, as well as deepen our comprehension for the nature of earthquake fault behavior and earthquake cycle. The Hellenic subduction zone and the earthquake-prone Crete, with large crustal motions of 3–4 cm/yr, may provide such a natural laboratory for this type of investigation. In this work, we examine the statistical structure and behavior of time series, as produced by permanent GPS sites, established on the islands of Crete and Gavdos.     

冲击加速度校准中低通滤波器的应用

介绍了在冲击加速度校准中,为了抑制电、机械等干扰和噪声对冲击加速度测量结果的影响,采用二阶巴特沃斯型低通滤波器,通过时间序列翻转、二次滤波等方式,实现零相移的低通滤波效果。并比较不同截止频率下,低通滤波器对衰减程度不同的冲击加速度波形产生的峰值偏差,给出不同加速度波形下,低通滤波器截止频率选择应注意的问题。     

Real-time coseismic wave retrieving by integrated Kalman filter with observations of GPS,Glonass and strong-motion sensor

A method of real-time coseismic wave retrieving was proposed based on the tight integration of GPS, Glonass and strong-motion sensor observations, the validation and precision analysis have been made by an experimental data. The series of results have been shown that: by the integrated Kalman filter and multi-sensors, the coseismic waves can be optimally recovered by complement the advantages of each other, especially when the observation conditions are very bad. In additional, the results are not significantly effected by different receiver clock error processes for the integration solution.     

变截面悬臂梁结构动载荷辨识方法

在航空航天领域，作用在结构上动载荷的确定对结构健康监测是非常必要和重要的。为此，本文以类似机翼结构的变截面悬臂梁结构为研究对象，提出了一种基于光纤光栅传感器与卡尔曼滤波器的动载荷识别方法。首先，根据变截面梁单元形式，推导出变截面梁的质量矩阵与刚度矩阵，建立动力学运动方程。然后，以光纤光栅传感器测得的应变信息作为观测信号，通过卡尔曼滤波器生成的增益矩阵、新息序列矩阵以及协方差矩阵，得到灵敏度矩阵和估计力的增益矩阵。在此基础上，利用广义回归模型及其最小二乘算法，估算出动载荷大小、判断出动载荷激励位置。借助数值仿真与实验手段，分别验证了该方法对于单点正弦激励、方波激励、锯齿波激励以及多点同时激励等工况下的动载荷识别效果。结果表明，本文所提算法具有较好的动载荷识别效果和噪声抑制能力，能够为未来风洞试验和真实飞行试验环境中诸如大展弦比机翼表面气动压力等载荷实时辨识、气动外形自适应控制以及结构健康监测提供技术支撑。     

Command filtered sliding mode trajectory tracking control for unmanned airships based on RBFNN approximation

This paper presents two sliding mode controllers to address the trajectory tracking problem of unmanned airships in the presence of unknown wind disturbance. The sliding mode controller proposed first is designed by a fast power rate reaching law(FPRRL). The disturbance is compensated by a radial basis function neural network (RBFNN). To avoid the aggressive adaptation, the controller is augmented by a command filter. The controller provides good robustness and tracking performance with no chattering under the hypothesis of ideal wind field. However, serious chattering occurs when simulation is performed under discontinuous wind field. To simulate the wind in practice, the wind field employed in the simulation is generated by the combination of a constant field and white noise. The controller is improved subsequently with an extended model to suppress the chattering induced by the white noise. The enhanced controller manipulates the derivation of system input, thus attenuating the chattering. Stability analysis shows that both controllers drive the tracking error into a controllable small region near zero. Simulations are provided to validate the performance of the proposed controllers under different wind hypothesis.