On-board correction of systematic error of Earth sensors

Infrared Earth sensors are used in spacecraft for attitude sensing. Their accuracy is limited by systematic and random errors. Dominant sources of systematic errors are analyzed for a typical scanning infrared Earth sensor used in a remote-sensing satellite in a 900-km Sun-synchronous orbit. The errors considered arise from seasonable variation of infrared radiation; oblate shape of the Earth; ambient temperature of sensors; changes in spin/scan period; and misalignment of the axis of the sensors. Simple relations are derived using least-squares curve fitting for onboard correction of these errors. With these, it is possible to improve the accuracy of attitude determination by eight fold and achieve performance comparable to ground-based post-facto attitude computation     

An autonomous celestial navigation method for LEO satellite based on unscented Kalman filter and information fusion

A reliable and secure navigation system and assured autonomous capability of satellite are in high demand in case of emergencies in space. Celestial navigation is a fully autonomous navigation method for satellite. To near earth satellite, the earth direction is the most important measurement and the horizon sensing accuracy is the most important factor which effects celestial navigation accuracy. According to the mode of acquiring horizon measurement, satellite celestial navigation methods can be broadly classified into two approaches: directly sensing horizon using earth sensor and indirectly sensing horizon by observation of starlight atmospheric refraction. For these two methods are complementary to each other, a new Unscented Kalman Filter (UKF) based information fusion method is proposed here for hybriding them. Compared to the traditional celestial navigation method, this method can provide better navigation performance and higher reliability. The hardware-in-loop test results demonstrate the feasibility and effectiveness of this method, in most cases the accuracy is sufficient for near earth civilian satellite and moreover it can be used as a backup system to provide redundancy.     

Onboard Attitude Error Computation for Automatic Spin Axis Control of Bhaskara

The Indian experimental remote sensing satellite, Bhaskara, uses two horizon crossing sensors mounted at 45° and 135° with respect to spin axis for onboard roll error computation and automatic control of the spin axis orientation within 3° of the orbit normal. A new method for roll error computation and control and digital hardware for the same are described. The system has flexibility to vary the threshold, to adapt to altitude variations and various mission requirements, and to work with a single horizon sensor. Flight performance of the system is satisfactory.     

基于衍射光栅的光纤光栅传感器解调系统研究

研究并实现了一种基于双衍射光栅的光纤布拉格光栅（FBG）传感器解调系统。该解调系统的光路由准直镜、衍射光栅、柱面反射镜和光电探测器等器件组成。通过准直镜后不同波长的平行光束经过衍射光栅后在空间展开,通过柱面反射镜聚焦在光电探测器成像面上。该光路通过采用两块衍射光栅的方法在减小解调系统尺寸的同时提高光学空间分辨力,采用线阵探测器替代扫描机构从而简化系统结构。从理论上分析了光束经过该系统后的空间光强分布,根据光强的高斯分布采用多项式拟合的方法实现了反射光谱峰值定位算法。通过与高精度光谱仪的测量结果对比表明,该解调方法具有较高的波长解调精度和稳定性。     

热激励谐振式硅微结构压力传感器温度场研究

针对一种以方形硅膜片为一次敏感元件、硅梁谐振子为二次敏感元件 ;采用电阻热激励、压敏电阻拾振的压力微传感器 ,分析了其工作机理 ;依幅值、相位条件讨论了该谐振式微传感器的闭环自激系统 ;建立了微传感器的温度场模型和热应力模型 ,并进行了仿真计算与分析     

Evaluating sensor technology for UAS collision avoidance

The problem of "sense-and-avoid" for Unmanned Aircraft Systems (UAS) is genuinely multi-dimensional: there is a wide range of UAS sizes, speeds, and maneuverability, as well as missions for which these UAS will be used. There are also a variety of sensors that might be used for sense-and-avoid, which have widely varying capabilities to measure distance or angle to an obstacle, as well as closing rate, and time to collision. Most sensors are not able to provide all required information about the geometry of an encounter; therefore, using a combination of sensors offers one possible solution. We are investigating the concept that there may be a variety of possible sensor solutions for each distinct UAS capability or mission. By studying the breadth of UAS types and missions, and selectively testing certain sensors in the field, we are evaluating the limits to the capabilities of sensors and sensor combinations. This report is on the progress of this multi-dimensional evaluation. We have scoped the dimensions for evaluating UAS capabilities and the capabilities of sensors. We are experimentally evaluating sensor parameters on a variety of aircraft to validate the specified capabilities. This reports on our methodology for field evaluation of sensor technology and the lessons learned on evaluation platforms and capabilities.     

台速度估计(英文)

针对惯性稳定平台中高精度和高带宽的速度信号需求,提出了基于低成本MEMS传感器的最优速度估计算法。采用一种新颖的传感器组合形式,包括一个低带宽的MEMS陀螺和两个低性能的MEMS加速度计。陀螺由于自身动态特性的影响,主要提供速度的低频信息,加速度计组合则由于自身偏置的影响,主要提供速度的高频信息,而估计器将两者信号进行融合。实验表明:最优状态估计器能够在时频域上,提供无偏的、高性能的速度信号。同时,在单自由度微型惯性稳定平台的应用过程中,其控制性能得到了相应的提高。该算法也适用于机器人控制、姿态估计和摩擦补偿等领域。     

A new distributed constant false alarm rate detector

A new constant false alarm rate (CFAR) test termed signal-plus-order statistic CFAR (S+OS) using distributed sensors is developed. The sensor modeling assumes that the returns of the test cells of different sensors are all independent and identically distributed In the S+OS scheme, each sensor transmits its test sample and a designated order statistic of its surrounding observations to the fusion center. At the fusion center, the sum of the samples of the test cells is compared with a constant multiplied by a function of the order statistics. For a two-sensor network, the functions considered are the minimum of the order statistics (mOS) and the maximum of the order statistics (MOS). For detecting a Rayleigh fluctuating target in Gaussian noise, closed-form expressions for the false alarm and detection probabilities are obtained. The numerical results indicate that the performance of the MOS detector is very close to that of a centralized OS-CFAR and it performs considerably better than the OS-CFAR detector with the AND or the OR fusion rule. Extension to an N-sensor network is also considered, and general equations for the false alarm probabilities under homogeneous and nonhomogeneous background noise are presented.     

激光诊断技术在脉冲爆震发动机研究中的应用

在美国海军研究生院及斯坦福大学的脉冲爆震发动机（PDE）模型上，应用两种新发展的二极管激光诊断技术－光吸收／高温辐射组合测定法和多路复合可调二极管激光（TDL）技术，测量了其中的温度、各燃烧产物组分等重要参数，并与传统方法所得结果进行对比，说明新方法可靠、准确，适合爆震燃烧流场这种特殊环境，测量精度更高，而且更加简便、快捷。     

Tracking a maneuvering target using sensors of variable quality

In an environment subject to sudden change, the accuracy of tracking and prediction is strongly influenced both by the sensor architecture and by the quality of the sensors. An image-enhanced algorithm is presented for both path following and covariance estimation in applications where the sensors are subject to sudden and unpredictable variation in quality. For an illustrative trajectory, the performance of the algorithm is contrasted with an extended Kalman filter (EKF) and an image-enhanced algorithm based upon the nominal sensors     

基于比例阀门的升降速度控制方法研究

提出了一种新的航空升降速度标准信号自动产生方法.从控制方面,采用硅压阻模拟、石英数字双传感器,分别作为过程控制传感器和基准压力传感器,保证系统升降速度的准确度.采用双闭环控制方案,模拟闭环采用电路设计实现,数字闭环通过计算机、数字传感器和软件实现.控制执行部件采用一对比例电磁阀门.控制电路设计采用了模拟电路PID和数字PID控制结合的串级控制方案,对实现升降速度和压力信号变化的微分电路进行了设计.实验证明,该装置升降速度的输出准确度优于0.2%F.S,控制范围为0～200 m/s.     

基于奇偶方程的FADS传感器故障检测方法

重复使用运载器（RLV）的嵌入式大气数据传感系统（FADS）中传感器的高可靠性是RLV飞行控制系统高可靠性的保障。结合FADS采用多个测压点冗余配置的特点,利用各传感器测量值之间存在的解析冗余关系,设计奇偶方程,实现对各个测压点故障传感器的有效检测。     

Detection by incoherent recombination with partial information

Matched filter (MF) detection in spread environments is often seriously degraded by the mismatch between the waveform replica and the composite signal formed by the spreading environment. Typically the spreading is caused by multiple delayed reflections due to scatter extent or multipath especially in shallow water sonar applications. It is possible to recover some detector performance by incoherent summation of weighted MF realizations in a process called incoherent recombining (IR). Several IR strategies for Gaussian data that assume varying amounts of prior scattering function (SF) information are examined, their receiver operating characteristics (ROCs) computed, and compared with those of the unrealizable “prescient” receiver (PR). They include optimally weighted and unweighted versions of the maximum likelihood estimator-correlator (EC), and variations of the “at-least-one” (ALO) detector that examines sequences of MF realizations declaring a detection if at least one threshold is crossed. As might be expected, performance improves with the accuracy of the prior information incorporated in the detector formulation     

Design of on-board calibration methods for a digital sun sensor based on Levenberg–Marquardt algorithm and Kalman filters

Digital sun sensor is one of the most important sensors used in the Attitude Determination System (ADS) of the satellite. Due to the harsh environmental conditions that exist in the space, various distortions may occur in the sun sensor optical system that lead to the reduced accuracy of this equipment. So, it is necessary to recalibrate the optical parameters of the aforementioned sensors. For this purpose, first a novel attitude independent error model is proposed for the SS-411 sun sensor that includes the central point of the CCD array, installation error, filter thickness and sensor misalignment. So, the mutual interfaces between the sensor parameters are considered in the developed model. In order to extract the sensor parameters, a nonlinear optimization technique called the Levenberg–Marquardt is applied to the developed model as a batch algorithm. In addition, the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF) have been utilized as sequential strategies. It will be shown that by considering a worst case of variation amount for sensor parameters, an accuracy improvement of about 17° is achieved by the developed calibration algorithms. Comparison between the developed algorithms represents that UKF has higher accuracy, shorter time convergence but higher computational load.     

A multi-rate sensor fusion approach using information filters for estimating aero-engine performance degradation

Gas-path performance estimation plays an important role in aero-engine health management, and Kalman Filter(KF) is a well-known technique to estimate performance degradation. In previous studies, it is assumed that different kinds of sensors are with the same sampling rate, and they are used for state estimation by the KF simultaneously. However, it is hard to achieve state estimation using various kinds of sensor measurements at the same sampling rate due to a complex network and physical characteristic differences between sensors, especially in an advanced multisensor architecture. For this purpose, a multi-rate sensor fusion using the information filtering approach is proposed based on the square-root cubature rule, which is called Multi-rate Squareroot Cubature Information Filter(MSCIF) to track engine performance degradation. Soft measurement synchronization of the MSCIF is designed to provide a sensor fusion condition for multiple sampling rates of measurement, and a fault sensor is isolated by maximum likelihood validation before state estimation. The contribution of this paper is to supply a novel multi-rate informationfilter approach for sensor fault tolerant health estimation of an aero-engine in a multi-sensor system. Tests are conducted for aero-engine performance degradation estimation with multiple sampling rates of sensor measurement on both digital simulation and semi-physical experiment.Experimental results illustrate the superiority of the proposed algorithm in terms of degradation estimation accuracy and robustness to sensor failure in a multi-sensor system.     

风扇/压气机周向模态识别中传感器角度偏差的影响

基于任意角度压缩感知(CS)方法分析了传感器安装角度偏差对风扇/压气机周向模态识别重构的影响,设计了一套自适应角度优化程序修正重构误差。利用数值试验探究了传感器角度偏差和数量对周向模态重构结果的影响,研究表明:当角度偏差等级为2.5%时,平均重构误差达到10%以上,若保证重构误差基本不变,将传感器数量从7个增加至25个,仅可以将角度偏差等级放宽至4%。而采用小生境微种群遗传算法进行自适应角度优化,在20 dB信噪比下,通过自适应角度优化可将角度偏差等级从2.5%放宽至10%,降低了传感器安装的精度要求。成功优化了一款冷却风扇在前三阶叶片通过频率下的主要周向声模态重构幅值。自适应角度优化算法有效提升了基于压缩感知的风扇/压气机周向模态重构可靠性。     

基于惯性/偏振光/光流的六足步行机器人自主导航方法研究

针对惯性/卫星组合导航系统易受干扰或自主性不足等问题，引入偏振光传感器和光流传感器，分别建立航向角和速度量测方程，以辅助惯性导航系统，提出了一种基于惯性/偏振光/光流的自主导航方法。同时，为实现惯性传感器、偏振光传感器和光流传感器等多传感器的融合，设计了无迹Kalman滤波器。为验证该方法的有效性，以六足步行机器人为对象开展仿真和实验验证。结果表明，在没有卫星信号源的情况下，仅依靠机器人自身感知，可实现较高精度的机器人位姿估计，实现了不依赖于卫星导航信号的自主导航，提升了导航系统的自主性。     

Multisensor resource deployment using posterior Cramer-Rao bounds

The development of a general framework for the systematic management of multiple sensors in target tracking in the presence of clutter is described. The basis of the technique is to quantify, and subsequently control, the accuracy of target state estimation. The posterior Cramer-Rao lower bound (PCRLB) provides the means of achieving this aim by enabling us to determine a bound on the performance of all unbiased estimators of the unknown target state. The general approach is then to use optimization techniques to control the measurement process in order to achieve accurate target state estimation. We are concerned primarily with the deployment and utilization of limited sensor resources. We also allow for measurement origin uncertainty, with sensor measurements either target-generated or false alarms. An example in which the aim is to track a submarine by deploying a series of constant false-alarm rate passive sonobuoys is presented. We show that by making some standard assumptions, the effect of the measurement origin uncertainty can be expressed as a state-dependent information reduction factor which can be calculated off-line. This enables the Fisher information matrix (FIM) to be calculated quickly, allowing Cramer-Rao bounds to be utilized for real-time, dynamic sensor management. The sensor management framework is shown to determine deployment strategies that enable the target to be accurately localized, and at the same time efficiently utilize the limited sensor resources.     

热激励谐振式硅微结构压力传感器

对一种以方形硅膜片作为一次敏感元件,硅梁作为二次敏感元件的热激励硅谐振式压力微传感器进行了较系统的研究 :建立了微传感器敏感结构的工程用数学模型;以所建立的模型实际设计了敏感结构参数 :方形膜边长 4 mm,膜厚 0.1 mm,梁谐振子长 1.3mm,宽 0.0 8mm,厚 0.0 0 7mm;采用微机械加工工艺加工出了原理样件;采用电热激励、压阻拾振方式对其进行了开环测试     

双端固支石英振梁力频系数与热弹性品质因数分析

双端固支石英振梁作为微型谐振式石英传感器的核心敏感元件,其力频系数和品质因数对传感器的灵敏度和分辨率具有重要的影响。石英振梁的力频系数越高,同等条件下传感器的灵敏度也越高;振梁品质因数越高,传感器的分辨力亦越高。对于工作于一阶振动模态的石英振梁而言,力频系数与热弹性品质因数仅与其自身的结构尺寸参数有关。通过分析发现,石英振梁的力频系数与热弹性品质因数之间存在一定的矛盾。详细分析了石英振梁力频系数与热弹性品质因数的特点及两者之间的定量影响,给出了两者的理论模型与仿真方法,建立了力频系数-热弹性品质因数的目标优化函数。分析结果表明,在音叉尺寸范围内,目标优化函数值从0.064增加为0.64,且变化趋势与品质因数相类似。最后,分析了在设计用于微型谐振式石英传感器的双端固支石英振梁时该如何获得最佳的传感器性能。