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Research of Multi-sensor Integrated Navigation Algorithm Aided by CNS/SAR

机译：CNS / SAR辅助的多传感器组合导航算法研究

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The technology of Digital Scene Matching Feature Correlation (DSMFC) hasrnbeen developed very quickly, which can modify the errors of Inertial Navigation Systemrn(INS) and reduce the navigation errors in terminal navigation enormously, and which hasrnbeen successfully applied in practice. But in other areas, such as the middle or globalrnnavigation, because of the images matching position needing the unequal matchingrncalculation time and the capability limitation of the airborne digital map database, DSMFCrnmay not be good enough for these applications. The navigation errors of the celestialrnnavigation system (CNS) do not accumulate along with time, so the technology has beenrnemphasized and extensively applied, and it has become the important autonomy navigationrnmeasure technique in aeronautics and astronautics areas. In practice application, CNS needsrnobserving the information of stars, but the information of stars probably can not bernobserved sometimes. Moreover, subjected by the horizontal attitude bench mark accuracy,rnthe navigation accuracy of CNS can’t reach the accuracy of GPS. So the application of CNSrnis limited in practice. If the imaging sensor of DSMFC is Synthetic Aperture Radar (SAR),rnwhich can normally work in all-weather and acquire real-time images, the application ofrnDSMFC may not be affected by weather and normally work in all-weather.rnBecause the GPS/INS integrated navigation system is easily interfered byrnelectromagnetic techniques, it is disadvantage for long-time autonomy navigation work.rnWhen GPS is denied or unavailable, we must have an alternative to GPS. And the INS/CNSrnor INS/SAR may be a good choice. Firstly, we can apply SAR to images matching positionrnand get the real-time position and course information of aircraft relative to the present flightrnpath, and apply CNS to get the position information of aircraft autonomously. Secondly, werncan integrate all information of CNS, SAR and INS to construct the CNS/SAR/INSrnintegrated navigation system based on INS, which has the outstanding global autonomyrnnavigation and terminal precise navigation abilities.rnIn order to overcome the possible electromagnetic interference in high altitude andrnlong-time navigation, and mainly through the autonomy technology to improve thernnavigation system accuracy, this paper describes the possibility and the navigationrnperformance of the CNS/INS integrated navigation system aided by SAR, which may bernused in large, high-altitude and long-distance transporter or unmanned aerial vehicle.rnConsidering the work characteristic of CNS and SAR, this paper proposes the systemrnscheme, and then gives the suitable multi-sensor integrated navigation algorithm, which canrnsolve the multi-sensor information fusion problem of asynchronous measurementrninformation. The results have verified the scheme and algorithm which can effectivelyrnintegrate the measurement information of INS, CNS and SAR, and meet the performancernneeds of global autonomy navigation accuracy. The CNS/INS integrated navigation systemrnaided by SAR has high autonomy navigation accuracy.
机译：数字场景匹配特征相关技术（DSMFC）发展迅速，可以修正惯性导航系统（INS）的误差，大大减少终端导航中的导航误差，已在实践中成功应用。但是在其他领域，例如中间或全局导航中，由于图像匹配位置需要不相等的匹配计算时间以及机载数字地图数据库的功能限制，因此DSMFC对于这些应用可能不够好。天体导航系统（CNS）的导航误差不会随着时间的推移而累积，因此该技术已得到重视和广泛应用，已成为航空航天领域重要的自主导航技术。在实际应用中，CNS需要保留恒星信息，但有时可能无法保留恒星信息。此外，受水平姿态基准精度影响，CNS的导航精度无法达到GPS的精度。因此，CNSrnis的应用在实践中受到限制。如果DSMFC的成像传感器是合成孔径雷达（SAR），它可以在全天候正常工作并获取实时图像，则DSMFC的应用可能不受天气的影响，并且可以在全天候正常工作。 INS组合导航系统容易受到电磁技术的干扰，不利于长时间的自主导航工作。当GPS被拒绝或无法使用时，我们必须有GPS的替代方案。 INS / CNSrnor INS / SAR可能是一个不错的选择。首先，可以将SAR应用于与位置信息匹配的图像，获取飞机相对于当前飞行路径的实时位置和航向信息，并应用CNS自主获取飞机的位置信息。其次，我们可以整合CNS，SAR和INS的所有信息，构建基于INS的CNS / SAR / INS组合导航系统，该系统具有出色的全球自主导航能力和终端精确导航能力。rn为了克服高空和长距离可能产生的电磁干扰导航，主要是通过自主技术来提高导航系统的精度，本文描述了SAR辅助的CNS / INS组合导航系统的可能性和导航性能，可能会在大型，高空，长途运输车中使用针对CNS和SAR的工作特点，提出了系统方案，然后提出了合适的多传感器集成导航算法，可以解决异步测量信息的多传感器信息融合问题。实验结果验证了该方案和算法能够有效地融合INS，CNS和SAR的测量信息，满足全球自主导航精度的性能需求。 SAR辅助的CNS / INS组合导航系统具有较高的自主导航精度。

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