Online INS/GPS integration with a radial basis function neural network

Most of the present navigation systems rely on Kalman filtering to fuse data from global positioning system (GPS) and the inertial navigation system (INS). In general, INS/GPS integration provides reliable navigation solutions by overcoming each of their shortcomings, including signal blockage for GPS and growth of position errors with time for INS. Present Kalman filtering INS/GPS integration techniques have some inadequacies related to the stochastic error models of inertial sensors, immunity to noise, and observability. This paper aims to introduce a multi-sensor system integration approach for fusing data from INS and GPS utilizing artificial neural networks (ANN). A multi-layer perceptron ANN has been recently suggested to fuse data from INS and differential GPS (DGPS). Although being able to improve the positioning accuracy, the complexity associated with both the architecture of multi-layer perceptron networks and its online training algorithms limit the real-time capabilities of this technique. This article, therefore, suggests the use of an alternative ANN architecture. This architecture is based on radial basis function (RBF) neural networks, which generally have simpler architecture and faster training procedures than multi-layer perceptron networks. The INS and GPS data are first processed using wavelet multi-resolution analysis (WRMA) before being applied to the RBF network. The WMRA is used to compare the INS and GPS position outputs at different resolution levels. The RBF-ANN module is then trained to predict the INS position errors and provide accurate positioning of the moving platform. Field-test results have demonstrated that substantial improvement in INS/GPS positioning accuracy could be obtained by applying the combined WRMA and RBF-ANN modules.     

Multimodule parallel series-loaded resonant converters

The design and implementation of a multimodule parallel series-loaded resonant (SLR) converter system is presented. The SLR converter to be paralleled is operated in the n=2 discontinuous mode (DCM). Its dc analysis and dynamic modeling are made. In parallel operation, an average control technique is proposed to compensate the mismatch in current control characteristics of each parallel converter. Good dynamic and static current sharing characteristics are obtained. In addition, to obtain good output voltage regulating control performance, a design procedure is presented to find the parameters of feedback voltage controller according to the prescribed specifications     

Development and verification of an innovative photomultiplier calibration system with a 10-fold increase in photometer resolution

In this study, we construct a photomultiplier calibration system. This calibration system can help scientists measuring and establishing the characteristic curve of the photon count versus light intensity. The system uses an innovative 10-fold optical attenuator to enable an optical power meter to calibrate photomultiplier tubes which have the resolution being much greater than that of the optical power meter. A simulation is firstly conducted to validate the feasibility of the system, and then the system construction, including optical design, circuit design, and software algorithm, is realized. The simulation generally agrees with measurement data of the constructed system, which are further used to establish the characteristic curve of the photon count versus light intensity.     

Novel AC line conditioner for power factor correction

A new ac line conditioner is presented for high input power factor and clean ac output voltages for isolating the linear or nonlinear loads. A three-phase two-leg switching mode rectifier with neutral-point-clamped topology is proposed to draw the sinusoidal line currents from the ac mains. The carrier-based current controller is used in the inner control loop to track the line current commands with unity power factor. The dc bus voltage controller is adopted in the outer control loop to regulate the dc-link voltage. A voltage compensator is used to balance the neutral point voltage on the dc tank. A three-phase two-leg inverter with neutral-point-clamped topology is adopted in the system to provide the clean ac output voltages to the critical or sensitive loads. The carrier-based current control scheme is adopted to improve the instantaneous output voltages. Experimental results show the validity and effectiveness of the proposed control strategy.     

Wavelet de-noising for IMU alignment

Inertial navigation system (INS) is presently used in several applications related to aerospace systems and land vehicle navigation. An INS determines the position, velocity, and attitude of a moving platform by processing the accelerations and angular velocity measurements of an inertial measurement unit (IMU). Accurate estimation of the initial attitude angles of an IMU is essential to ensure precise determination of the position and attitude of the moving platform. These initial attitude angles are usually estimated using alignment techniques. Due to the relatively low signal-to-noise ratio of the sensor measurement (especially for the gyroscopes), the initial attitude angles may not be computed accurately enough. In addition, the estimated initial attitude angles may have relatively large uncertainties that may affect the accuracy of other navigation parameters. This article suggests processing the gyro and accelerometer measurements with multiple levels of wavelet decomposition to remove the high frequency noise components. The proposed wavelet de-noising method was applied on a navigational grade inertial measurement unit (LTN90-100). The results showed that accurate alignment procedure and fast convergence of the estimation algorithm, in addition to reducing the estimation covariance of the three attitude angles, could be obtained.     

Tracking multitarget in cluttered environment

A method for multitarget tracking and initiating tracking in a cluttered environment is proposed. The algorithm uses a sliding window of length uT (T is the sampling time) to keep the measurement sequence at time k. Instead of solving a large problem, the entire set of targets and measurements is divided into several clusters so that a number of smaller problems are solved independently. When a set of measurements is received, a new set of data-association hypotheses is formed for all the measurements lying in the validation gates within each cluster from time K-u+1 to K. The probability of each track history is computed, and, choosing the largest of these histories, the target measurement is updated with an adaptive state estimator. A covariance-matching technique is used to improve the accuracy of the adaptive state estimator. In several examples, the algorithm successfully tracks targets over a wide range of conditions     

Constructive neural-networks-based MEMS/GPS integration scheme

This article exploits the idea of developing an alternative data fusion scheme that integrates the outputs of low-cost micro-electro-mechanical systems (MEMS) inertial measurements units (IMUs) and receivers of the global positioning system (GPS). The proposed scheme is implemented using a constructive neural network (cascade-correlation network (CCNs)) to overcome the limitations of conventional techniques that are predominantly based on the Kalman filter (KF). The CNN applied in this research has the advantage of having a flexible topology if compared with the recently utilized multi-layer feed-forward neural networks (MFNNs) for inertial navigation system (INS)/GPS integration. The preliminary results presented in this article illustrate the effectiveness of proposed CCNs over both MFNN-based and Kalman filtering techniques for INS/GPS integration.     

基于特征增维和近邻成分分析的民航发动机故障分类方法

为提高航空发动机故障诊断准确度,提出了一种从快速存取记录器（QAR）数据中提取最合适故障特征的方法。对原始QAR数据进行缺失值填补和巡航点提取操作,选择部分发动机性能参数差值作为初始特征值;再采用特征增维方法挖掘隐藏特征信息,进而采用近邻成分分析算法进行特征筛选优化,将所提方法与朴素贝叶斯等4种分类算法相结合,对某航空公司CFM56-7B发动机的QAR数据进行试验验证。结果表明：从QAR数据中提取最合适故障特征的方法能有效地提高发动机故障分类算法的准确率,且适用于不同的诊断算法,准确率优于80%。     

Soldier Identification System utilizing low probability ofintercept (LPI) techniques

This paper documents the design of a laser/radio frequency (RF) Soldier Identification (ID) System developed by Dynetics, Inc., Harris, Corp., and the US Army Communications and Electronics Command (CECOM). The Soldier ID system includes an Interrogation Unit with a programmable activation code. The Interrogation Unit consists of a directive, eye-safe laser and a spread-spectrum RF transceiver. This allows for a low probability of intercept (LPI) interrogation, which is of interest during covert operations. A Responder Unit is worn, for example, by a soldier and transmits an LPI spread-spectrum RF response, only after receiving the proper interrogation codes. The basic subsystems for the identification system are a Laser Interrogation Unit, an RF Responder Unit, and an electronic Programming Unit. The operating principles for the subsystem are reviewed, and the design issues are discussed. In addition to the preliminary design performed under Phase I of the program, a breadboard system was developed to validate the proof-of-principle concept. Hardware implementation is reviewed and test results are presented. The brassboard development and engineering plans are also presented