基于GPS的弹射试验测试系统研究
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摘要
弹射座椅是在紧急情况下将飞行员弹射出舱并带离危险区以获得救生的设备。弹射座椅在设计定型前要经过大量的试验以验证其各项救生性能。目前弹射试验主要依靠光测和遥测。基于GPS的位置、速度测量是一种先进的测试技术,将其与先进的数据处理技术相结合可以实现一种新的弹射救生试验测试技术,构建功能强大的测试系统,对于航空试验测量有重要理论和实际意义。
     为方便测试结果的定义和转换,工程测试系统首先要建立其时间和空间参考。基于GPS的测试系统涉及到多种时间和空间参考系统。本文首先定义了测试系统的时间参考和空间参考,确定其与各种GPS时间和空间参考系统的转换关系。
     基于GPS的弹射试验测试系统主要由地面GPS测试基准站、地面数据处理计算机和机载测试装置三部分组成。地面基准站与机载测试装置共同构成差分定位方式。由于测试结果由数据后处理获取,没有实时性的要求,因此机载测试装置与基站间不设数据通信链路,所有的测试数据都同步保存到测试设备中以便事后处理使用。
     适宜的定位算法可以有效地提高定位测试精度,本文根据对象的动态特性选用载波相位差分算法以获得优良的测试性能。事后数据处理使用的是GPS-OEM板的原始测量数据,以获得更高的数据更新率。为了避免误判和漏判消息帧,对原始二进制数据流进行解码以获得测量数据和卫星星历时使用了滑窗算法。本文采用站际、星际双差观测模型进行载波相位差分定位解算。
     随机噪声的影响会给系统引入测试误差,这种误差对于基站和测站没有相关性,无法通过差分运算进行消除或减弱。数据平滑和滤波可以有效减少随机噪声带来的误差。观测信息的冗余是进行数据平滑的前提,应用最小二乘准则对单历元观测信息进行纵向平滑,以减小观测误差。卡尔曼滤波属于最优估计滤波。它可以在含有噪声的信号中估计出系统真实的状态。但是卡尔曼滤波只有在建立较准确的系统模型和观测模型的情况下才是最佳的。当系统的滤波模型与实际不匹配时,会使滤波精度下降,严重的还会导致滤波发散。本文结合测试对象的高动态特性,对不同系统模型的滤波效果进行了仿真分析,并采用了对象的“当前”统计滤波模型和自适应滤波算法,仿真结果和实际试验结果表明,该方案获得了良好的滤波效果。
     通过大量的试验研究表明,将GPS应用于弹射轨迹的试验测试是可行的,用适宜的定位算法和滤波算法可以获得亚米级精度。但对于高动态的试验环境,如何解决卫星失锁将是工程应用中必须解决的问题,本论文最后探讨了几种可用于工程应用的地面增强系统。
     本论文的创新工作主要包括:
     1、将GPS差分定位技术引入到弹射救生试验测试中,产生了新的弹射试验测试方法,提高了测试水平和测试的自动化程度。
     2、将静态差分定位的后处理手段和动态差分定位测试有机结合,解决了动态精确定位、测速问题。
     3、同时使用纵向平滑和横向平滑的滤波算法,建立了加速度“当前”统计模型的Kalman自适应滤波算法,有效提高了测试数据的后处理的抗干扰能力和测试精度。
     随着GPS现代化计划,以及GLONASS和Galileo(伽利略)系统的建设,卫星定位将会在弹射试验测试中发挥更加突出的作用。
Ejection seat is a device which rescues the pilot by taking him out of the danger in case of emergency. Plenty of tests must be done to validate every life-support performance before finalizing the design of ejection seat. Currently the ejection test relies on photo-graphic measurement and radio remote measurement. GPS-based position & velocity testing device is an advanced test technology. Integrated with advanced data processing technology, a new ejection test technology can be applied, and a powerful test system can be build. It is significative on theory and practicality for aviation test measurement.
     To convenience the definition and conversion of test result, time reference and space reference must be defined firstly on engineering test. There are some kinds of time-references and space-references involved in GPS-based test system. Firstly this dissertation defined time-reference and space-reference of ejection test system.
     GPS-based ejection test system consists of three parts, which includes ground GPS test base station, ground data process computer and airborne test station. The ground base station and airborne test station make of differential GPS position. Because the test result acquired by post data process, so there is no real-time process demand. There is no data link layer between ground base station and airborne test station. All test data must be stored into test device synchronously so it can be process after test.
     Proper position algorithm can improve the test performance effectively. According the dynamic characteristics of the testing target, this dissertation presents post-process algorithm of carrier phase to improve test performance. Post data process uses the raw measurements provided by the GPS-OEM receiver to acquire higher data rate. To avoid missing and losing message frame, it adopts slide-window algorithm to code the binary data stream and to acquire measurement data and ephemeris data. This dissertation adopts double-difference observe model between station and satellite to resolve carrier phase differential position.
     Because of weak correlativity between base station and airborne station, the test error introduced by random noise can not be eliminated or weakened by differential algorithm. It can be eliminated effectively by adjustment value and filtering. Redundancy of measurements is the pre-condition of adjustment value. Apply least square law to long-direction adjust the single epoch measurement to minish the observe error. The Kalman filter is the best optimal estimator. It can estimate the true state of the system from signals including noise. But the Kalman filter works effectively only in case of building an accuracy process model and measurement model. When the filtering model can not match the actual system, the filtering precision decreased, badly it can cause filtering diverging. Based on the characteristics of the testing target, this dissertation analyses and simulates the filtering effect under different system models; and adopted the current statistical models of acceleration and adaptive Kalman algorithm. The simulation results and actual test filtering results indicate that the testing precision be improved effectively.
     According plenty of test researches, it is feasible that apply GPS to ejection test; Proper position algorithm and filtering algorithm can acquire sub-meter precision. It must be resolved in engineering application that how to settle the lost-lock of the signal of satellites under the high dynamic test condition. Finally this dissertation discusses some ground enhanced systems that can be used in engineering application.
     The innovation works of the dissertation including:
     1. Introduced differential GPS position into ejection test, produced new test means, improved test proformance and test automatization.
     2. Integrated the post-process of static differential position and dynamic differential position, solved the problem of dynamic position and velocity measurement.
     3. Used the long-direction and lateral-direction adjustment filtering algorithm; built the current statistical model of acceleration and adaptive Kalman algorithm, improved the anti-jamming of post data process and test performance.
     In company with the project of GPS modernization and the construction of GLONASS and Galileo, satellite-position will play more important role on the ejection test.
引文
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