A fast pulse phase estimation method for X-ray pulsar signals based on epoch folding

X-ray pulsar-based navigation (XPNAV) is an attractive method for autonomous deep-space navigation in the future. The pulse phase estimation is a key task in XPNAV and its accuracy directly determines the navigation accuracy. State-of-the-art pulse phase estimation techniques either suffer from poor estimation accuracy, or involve the maximization of generally non-convex object function, thus resulting in a large computational cost. In this paper, a fast pulse phase estimation method based on epoch folding is presented. The statistical properties of the observed profile obtained through epoch folding are developed. Based on this, we recognize the joint prob-ability distribution of the observed profile as the likelihood function and utilize a fast Fourier transform-based procedure to estimate the pulse phase. Computational complexity of the proposed estimator is analyzed as well. Experimental results show that the proposed estimator significantly outperforms the currently used cross-correlation (CC) and nonlinear least squares (NLS) estima-tors, while significantly reduces the computational complexity compared with NLS and maximum likelihood (ML) estimators.     

DME Interference mitigation for L-DACS1 based on system identification and sparse representation

L-band digital aeronautical communication system 1 (L-DACS1) is a promising candi-date data-link for future air-ground communication, but it is severely interfered by the pulse pairs (PPs) generated by distance measure equipment. A novel PP mitigation approach is proposed in this paper. Firstly, a deformed PP detection (DPPD) method that combines a filter bank, correlation detection, and rescanning is proposed to detect the deformed PPs (DPPs) which are caused by mul-tiple filters in the receiver. Secondly, a finite impulse response (FIR) model is used to approximate the overall characteristic of filters, and then the waveform of DPP can be acquired by the original waveform of PP and the FIR model. Finally, sparse representation is used to estimate the position and amplitude of each DPP, and then reconstruct each DPP. The reconstructed DPPs will be sub-tracted from the contaminated signal to mitigate interference. Numerical experiments show that the bit error rate performance of our approach is about 5 dB better than that of recent works and is closer to interference-free environment.     

Real-time object tracking via least squares transformation in spatial and Fourier domains for unmanned aerial vehicles

This paper addresses the problem of real-time object tracking for unmanned aerial vehicles. We consider the task of object tracking as a classification problem. Training a good classifier always needs a huge number of samples, which is always time-consuming and not suitable for realtime applications. In this paper, we transform the large-scale least-squares problem in the spatial domain to a series of small-scale least-squares problems with constraints in the Fourier domain using the correlation filter technique. Then, this problem is efficiently solved by two stages. In the first stage, a fast method based on recursive least squares is used to solve the correlation filter problem without constraints in the Fourier domain. In the second stage, a weight matrix is constructed to prune the solution attained in the first stage to approach the constraints in the spatial domain. Then, the pruned classifier is used for tracking. To evaluate proposed tracker's performance, comprehensive experiments are conducted on challenging aerial sequences in the UAV123 dataset. Experimental results demonstrate that proposed approach achieves a state-ofthe-art tracking performance in aerial sequences and operates at a mean speed of beyond 40 frames/s. For further analysis of proposed tracker's robustness, extensive experiments are also performed on recent benchmarks OTB50, OTB100, and VOT2016.     

几种生长模型参数的最小二乘估计方法及应用

提出一种Logistic模型、Gompertz模型、Mitscherlich模型和Bertallanffy模型的分布参数估计方法，这种方法以加权最小二乘法为基础，推导求解分布参数的方程组。利用这类曲线模型中参数形式的特点，使同时求解三个参数的问题简化为同时求解两个参数的问题，并给出求解参数耦合方程组的二重二分迭代法。预测地基沉降的计算实例表明，这种方法对于迭代初值的选取要求较低、求解速度快、精度高，而且通过选取权因子可以对已有数据实现“重近轻远”的处理。     

Semi-stochastic modification of second-order radial derivative of Abel–Poisson’s formula for validating satellite gravity gradiometry data

The geoid can be used to validate the satellite gravity gradiometry data. Validation of such data is important prior to their downward continuation because of amplification of the data errors through this process. In this paper, the second-order radial derivative of Abel–Poisson’s formula is modified stochastically to reduce the effect of the far-zone geoid and generate the second-order radial derivative of geopotential at 250 km level. The numerical studies over Fennoscandia show that this method yields the gradients with an error of 10 mE and when the long wavelength of geoid is removed from the estimator and restored after the computations (remove–compute–restore) the error will be in 1 mE level. We name this method semi-stochastic modification. The best case scenario is found when the degree of modification of the integral formula is 200 and the long wavelength geoid to degree 100 is removed and restored. In this case the geoid should have a resolution of 15′ × 15′ and the integration should be performed over a cap size of 3°.     

基于非线性变换的加速度计误差标定与补偿CSCD

为提高三轴加速度计测量精度,分析其误差来源和产生机理,建立了误差模型;根据误差模型和重力场幅值不变特性,推导出非线性观测方程。引入两个未知的参数向量,通过数学变换把非线性观测方程变形为关于新未知参数的线性方程;然后采用批量最小二乘法求出新的未知参数,并根据误差模型参数和新未知参数之间的关系,利用逆解析运算求出对应的零点偏差、灵敏度误差和三轴不正交误差。实验结果表明,加速度计正负误差峰值间距可以减小100倍左右,精度可达10-3m/s2,并具有很好的可重复性。该方法算法效率较高,补偿效果显著。     

基于卫星和星敏感器的冗余激光惯组在轨标定

采用高精度卫星导航速度、位置信息以及星敏感器提供的姿态信息设计十表冗余捷联惯组的标定模型,包含陀螺和加速度计的零次项和标度因数,对卫星和星敏感器辅助的冗余激光陀螺捷联惯组进行实时在轨标定.利用标准Kalman滤波和Sage-Husa自适应滤波作为估计算法,对十表冗余捷联惯组参数进行在线估计.数值仿真结果表明:参数标定精度均在7％以内,是一种实时的在轨标定方法,满足误差补偿要求.冗余惯组在轨标定方法为航天器高精度定姿和定轨提供了一种理论参考.     

基于雷达航迹的航空器质量估算

为保障基于轨迹运行的顺利实施,必须提高四维航迹预测的精度,而四维航迹的精准预测依赖于航空器质量准确估算。鉴于此,构建并分析了航空器能量模型;基于雷达航迹与航空器基础资料( BADA),提出了新型的航空器质量估算方法与步骤;利用最小二乘算法求解了航空器质量的估计值;分别基于预测航迹、雷达轨迹与QAR数据,采用相对误差作为评价指标,实施验证与分析。验证结果表明,提出的方法可将航空器质量估算误差控制在5%以内,从而能够有效地提高航迹预测精度。     

基于自回归与最小均方理论的振动环境下 光纤陀螺仪滤波方法

针对振动应力下光纤陀螺产生测量误差增大的问题,从振动对光纤环的影响机理出发,分析了振动应力下光纤陀螺干涉信号的表现形式,提出了基于自回归最小均方滤波理论的光纤陀螺滤波方法,将AR模型的平稳性和最小均方根滤波的自适应性相结合,提取平稳数据的特性参数,对高频信号进行滤波,降低非互易相移产生陀螺角速度误差值的干扰.试验表明,该方法简单可行,有效地降低了振动应力下光纤陀螺输出信息的噪声,抑制了由振动引起的陀螺漂移.     

民用大涵道比涡扇发动机压气机叶片重量估算方法

针对民用大涵道比涡扇发动机的设计特点,基于部件一维气动设计结果,分别建立高压压气机叶片(增压级、中压压气机叶片重量估算模型与高压压气机叶片相同)、风扇叶片重量估算模型:通过简化高压压气机叶片结构,采用等效厚度、气动修正因子等方法,建立了基于统计分析法的高压压气机叶片重量估算模型;通过分段简化风扇叶片结构,采用弦长、最大厚度拟合规律及分段求解体积等方法,建立了基于统计分析法的风扇叶片重量估算模型。