应用加权中值滤波法检测薄壁梁式挠性器件下摆量

应用加权中值滤波法对薄壁梁式挠性器件下摆量进行高准确度CCD检测。薄壁梁式挠性器件在测量过程中测量图像存在高频抖动现象,因此测量准确度不高,运用加权中值滤波后使用最小二乘法细分技术,可以在实现提高测量准确度的同时,消除高频抖动带来的误差,从而可以有效提高CCD测量薄壁梁式挠性器件下摆量的准确度。实验表明,该方法比传统测量方法准确度提高20倍以上。     

一种TASIMM-UKF导弹状态估计方法

为了提高对机动导弹状态估计的精度和速度,提出了一种三轴分离IMM-UKF(TASIMM-UKF)滤波算法。将导弹运动状态按坐标轴方向进行三轴分离,并基于CV,CA和CJ模型集,采用无迹卡尔曼滤波器并行估计导弹三轴状态信息,有效地解决了导弹不同运动轴间的模型竞争问题。仿真结果表明,该方法能有效提高状态估计精度,缩短了估计时间,对复杂大机动目标状态估计具有良好的性能。     

An improved approach for rainfall estimation over Indian summer monsoon region using Kalpana-1 data

In this paper, an improved Kalpana-1 infrared (IR) based rainfall estimation algorithm, specific to Indian summer monsoon region is presented. This algorithm comprises of two parts: (i) development of Kalpana-1 IR based rainfall estimation algorithm with improvement for orographic warm rain underestimation generally suffered by IR based rainfall estimation methods and (ii) cooling index to take care of the growth and decay of clouds and thereby improving the precipitation estimation.     

基于最小一乘的跑道入口高度计算

跑道入口高度是关系着飞机能否安全着陆的关键参数,在其计算中需要采用曲线拟合预测的方法。目前大多是采用基于最小二乘准则的拟合方式。由于最小二乘准则的局限性,当下滑道随机误差不满足正态分布,在飞行数据中出现异常点时会给预测带来较大误差。将最小一乘方法引入到跑道入口高度计算问题中,提高了算法的稳健性,很好地克服了这一问题。     

Soil moisture estimation by using multipolarization SAR image

In the past studies, different soil moisture estimation models were developed for bare soil areas by using remotely-sensed data. However, there are few models that can be used to estimate soil moisture in vegetated areas. Water Cloud Model (WCM) model is a widely used soil moisture estimation model has been developed for vegetated areas. In this study, the WCM model was extended to take soil roughness parameter into consideration. The modeling and its accuracy assessment were done by using multi-polarization Airborne Synthetic Aperture Radar (AIRSAR) images and ground data collected during field Soil Moisture Experiments.     

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.     

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。