Rhere exists a slope drifrion an integra gyro when it is used as an azimush gyro, which may cause serious heading and posirion erross in: be Inertial Navigation System (INS). Thereby, it is necessary to estimate and colmpensate ir. This paper describes its cause and characteristes. A methed of esing the output of INS after BBA CALTHRASION to estimase it and constant drift is discussed in detail. In addition. some issues needed to nore in the practical operation are provided too. Software-simniztion and practical experiment both show the valid-ty of this method.

This paper describes the features of an extended Kalman filter algorithm designed to support the navigational function of a real-time vehicle performance and emissions monitoring system currently under development. The Kalman filter is used to process global positioning system (GPS) data enhanced with dead reckoning in an integrated mode, to provide continuous positioning in built-up areas. The dynamic model and filter algorithms are discussed in detail, followed by the findings based on computer simulations as well as a limited field trial carried out in the Greater London area. The results of using the extended Kalman filter algorithm demonstrate that the integrated system employing GPS and low cost dead reckoning devices is capable of meeting the required navigation performance of the device under development.

该文研究了推算船位/罗兰C（GPS）组合导航系统的组合和推广的非线性卡尔曼滤波算法在试组合模式中的应用，详细推导了舰船运动的七状态教学模型及其机械编排。该文还给出了该组合系统在南海进行试验时的舰船轨迹及定位误差曲线，并进行了比较分析。结果表明：组合系统克服了推位系统的积累误差，抑制了罗兰C（GPS）的随机定位误差，有效地改善了导航定位精度，滹波方案正确，算法稳定。该组合系统已成功地装备于多种型号的舰船上。

Transport-related environmental problems continue to constitute a major challenge to policy makers at all levels. A key feature of these problems is that they arise from the interaction of human behavioral systems and physical systems. Thus, to improve our understanding of environmental and health problems associated with vehicle emissions it is necessary to combine data on both travel and traffic behavior with environmental data linked to the corresponding spatial and temporal variables. There are currently no such databases available. A new low-cost real-time device is currently under development utilizing the latest developments in environmental monitoring, navigation, communications, data mining and warehousing to capture spatio-temporally referenced data on vehicle and driver performance and the level of emissions and concentrations. Because of the need to acquire data in all environments, there are potential limitations in using a global satellite navigation system such as GPS to determine the spatial and temporal data in built-up areas. Therefore, an augmentation strategy involving differential GPS and new low-cost dead reckoning sensors utilizing micro-electromechanical systems technology has been explored. This paper presents a high-level description of the real-time vehicle performance and emissions monitoring system, and details the results of a study carried out to characterize the performance of stand-alone and augmented GPS, and assess whether the required navigation performance is achievable. The study characterized the performance of different types of stand-alone GPS receivers and GPS augmented with differential infrastructure and low-cost dead reckoning sensors. The performance indicators used were satellite visibility, coverage, accuracy and integrity. The results highlight the weaknesses and differences in performance, depending on the type of GPS receiver used and shows that, unlike GPS alone, an integrated system employing GPS and low-cost dead reckoning sensors is capable of meeting the required navigation performance in built-up areas. Furthermore, no significant difference in accuracy between standalone GPS and differential GPS has been seen.

介绍了多传感组合导航系统的设计方法，从系统功能、硬件结构、数据处理算法和故障检测等方面全面深入研究了分布式多机系统、联合滤波算法以及基于多传感器冗余方案的故障检测和隔离算法。本文设计的多传感器组合导航系统方案合理，数据处理精度高。算法计算量小，可靠性高、具有较高的工程实用价值。