GNSS-MR用于雪深監(jiān)測研究
發(fā)布時(shí)間：2018-08-06 10:28
【摘要】：GNSS測站周圍的環(huán)境會(huì)對其觀測值產(chǎn)生多路徑效應(yīng)影響,如何消除或削弱多路徑效應(yīng)一直受到廣大學(xué)者的關(guān)注。與此相反,隨著全球衛(wèi)星導(dǎo)航系統(tǒng)研究與應(yīng)用的不斷深入,以GNSS-MR技術(shù)為代表的基于多路徑效應(yīng)影響的信噪比信息反演測站周圍環(huán)境參數(shù)的課題成為一個(gè)新的研究熱點(diǎn),使得GNSS在地表遙感領(lǐng)域嶄露頭角。本文在國內(nèi)外學(xué)者研究的基礎(chǔ)上,從GNSS-MR技術(shù)基本原理出發(fā),將其應(yīng)用到雪深測量,并結(jié)合美國板塊監(jiān)測網(wǎng)絡(luò)原始觀測數(shù)據(jù)與SNOTEL雪深實(shí)測數(shù)據(jù),重點(diǎn)對GNSS-MR用于雪深測量的可行性與精度進(jìn)行研究分析。本文的主要研究內(nèi)容和成果如下:1、對多路徑效應(yīng)與信噪比特征進(jìn)行概述,討論了多路徑效應(yīng)與信噪比之間的關(guān)系。低高度角信噪比數(shù)據(jù)受多路徑效應(yīng)影響較大,通過多項(xiàng)式擬合的方法可以實(shí)現(xiàn)直射信號(hào)與多路徑反射信號(hào)的分離,進(jìn)而利用多路徑影響的信噪比信息實(shí)現(xiàn)地表環(huán)境參數(shù)的反演。2、對GNSS-MR技術(shù)的基本原理和計(jì)算流程進(jìn)行闡述,對雪深探測范圍與信號(hào)反射點(diǎn)軌跡進(jìn)行討論。GNSS-MR雪深探測范圍大約是1000m2;GNSS信號(hào)反射點(diǎn)軌跡一方面可以實(shí)現(xiàn)GNSS-MR雪深監(jiān)測的選星,一方面可以獲取到積雪的空間分布信息。3、證明了信噪比殘差序列的變化頻率與降雪厚度成負(fù)相關(guān)關(guān)系。并從單顆衛(wèi)星,多顆衛(wèi)星,長時(shí)間序列3方面,層層遞進(jìn),驗(yàn)證了GPS-MR雪深監(jiān)測算法的可行性,其測量精度可以達(dá)到0.1m。4、對GPS-MR雪深測量技術(shù)精度影響因素進(jìn)行分析,驗(yàn)證了合理的設(shè)置高度角范圍,采用具有較高接收功率的信噪比數(shù)據(jù)以及高采樣的數(shù)據(jù)都會(huì)對反演結(jié)果做出有益的貢獻(xiàn),其反演精度相對較高,反演結(jié)果也更加穩(wěn)定。5、介紹了Rinex3.X格式的新變化,利用MATLAB語言設(shè)計(jì)GNSS-MR雪深測量數(shù)據(jù)處理系統(tǒng),結(jié)合實(shí)測數(shù)據(jù)驗(yàn)證其正確性,并根據(jù)數(shù)據(jù)處理需求,輸出相應(yīng)的圖表文檔文件。當(dāng)前,多頻多模衛(wèi)星導(dǎo)航系統(tǒng)發(fā)展迅猛,世界各地的GNSS跟蹤站(如IGS,PBO,陸態(tài)網(wǎng)絡(luò)等)也如雨后春筍般建成,GNSS-MR技術(shù)的研究具備得天獨(dú)厚的資源與發(fā)展空間。隨著研究與技術(shù)不斷進(jìn)步與成熟,GNSS-MR這種全新的遙感手段在實(shí)時(shí)地表環(huán)境監(jiān)測(降雪、土壤濕度、海平面等)方面的應(yīng)用讓人期待!
[Abstract]:The environment around the GNSS station will have a multipath effect on its observation value. How to eliminate or weaken the multipath effect has been concerned by many scholars. On the contrary, with the development of the research and application of global satellite navigation system, the research on retrieving the environmental parameters around the station based on the signal to noise ratio (SNR) information based on multipath effect, represented by GNSS-MR technology, has become a new research hotspot. GNSS has made its mark in the field of remote sensing of the earth's surface. Based on the research of domestic and foreign scholars, this paper applies GNSS-MR technology to snow depth measurement, and combines the original observation data of American plate monitoring network and SNOTEL snow depth measurement data. The feasibility and accuracy of GNSS-MR for snow depth measurement are studied and analyzed. The main contents and results of this paper are as follows: 1. The characteristics of multipath effect and signal-to-noise ratio are summarized and the relationship between multipath effect and signal-to-noise ratio is discussed. The low altitude signal-to-noise ratio (SNR) data are greatly affected by multipath effect. The separation of direct and multipath reflected signals can be realized by polynomial fitting. Then using the signal-to-noise ratio (SNR) information of multipath influence to realize the inversion of surface environmental parameters, the basic principle and calculation flow of GNSS-MR technology are expounded. This paper discusses the range of snow depth detection and the track of signal reflection point. GNSS-MR snow depth detection range is about 1000m ~ (2) m ~ (2) GNSS-MR signal's reflection point trajectory. On the one hand, it can realize the selection of stars for GNSS-MR snow depth monitoring. On the one hand, the spatial distribution information of snow cover. 3 can be obtained, which proves that the variation frequency of SNR residuals is negatively related to the snowfall thickness. The feasibility of the GPS-MR snow depth monitoring algorithm is verified from three aspects of single satellite, multiple satellites and long time series. The accuracy of the algorithm can reach 0.1 m.4. the factors influencing the accuracy of GPS-MR snow depth measurement technology are analyzed. It is verified that setting the range of height angle reasonably, the SNR data with higher receiving power and the data with high sampling will all make beneficial contributions to the inversion results, and the inversion accuracy is relatively high. The inversion results are also more stable. 5. The new changes of Rinex3.X format are introduced. The GNSS-MR snow depth measurement data processing system is designed by using MATLAB language. The correctness of the system is verified by combining the measured data, and the corresponding chart document files are output according to the data processing requirements. At present, the multi-frequency and multi-mode satellite navigation system is developing rapidly, and the research of GNSS tracking stations (such as IGSS-PBO, land state network, etc.) all over the world has a unique resource and development space. With the development of research and technology, GNSS-MR, a new remote sensing tool, is expected to be used in real-time surface environment monitoring (snow, soil moisture, sea level, etc.).
【學(xué)位授予單位】：長安大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：P228.4;P407
本文編號(hào)：2167446
[Abstract]:The environment around the GNSS station will have a multipath effect on its observation value. How to eliminate or weaken the multipath effect has been concerned by many scholars. On the contrary, with the development of the research and application of global satellite navigation system, the research on retrieving the environmental parameters around the station based on the signal to noise ratio (SNR) information based on multipath effect, represented by GNSS-MR technology, has become a new research hotspot. GNSS has made its mark in the field of remote sensing of the earth's surface. Based on the research of domestic and foreign scholars, this paper applies GNSS-MR technology to snow depth measurement, and combines the original observation data of American plate monitoring network and SNOTEL snow depth measurement data. The feasibility and accuracy of GNSS-MR for snow depth measurement are studied and analyzed. The main contents and results of this paper are as follows: 1. The characteristics of multipath effect and signal-to-noise ratio are summarized and the relationship between multipath effect and signal-to-noise ratio is discussed. The low altitude signal-to-noise ratio (SNR) data are greatly affected by multipath effect. The separation of direct and multipath reflected signals can be realized by polynomial fitting. Then using the signal-to-noise ratio (SNR) information of multipath influence to realize the inversion of surface environmental parameters, the basic principle and calculation flow of GNSS-MR technology are expounded. This paper discusses the range of snow depth detection and the track of signal reflection point. GNSS-MR snow depth detection range is about 1000m ~ (2) m ~ (2) GNSS-MR signal's reflection point trajectory. On the one hand, it can realize the selection of stars for GNSS-MR snow depth monitoring. On the one hand, the spatial distribution information of snow cover. 3 can be obtained, which proves that the variation frequency of SNR residuals is negatively related to the snowfall thickness. The feasibility of the GPS-MR snow depth monitoring algorithm is verified from three aspects of single satellite, multiple satellites and long time series. The accuracy of the algorithm can reach 0.1 m.4. the factors influencing the accuracy of GPS-MR snow depth measurement technology are analyzed. It is verified that setting the range of height angle reasonably, the SNR data with higher receiving power and the data with high sampling will all make beneficial contributions to the inversion results, and the inversion accuracy is relatively high. The inversion results are also more stable. 5. The new changes of Rinex3.X format are introduced. The GNSS-MR snow depth measurement data processing system is designed by using MATLAB language. The correctness of the system is verified by combining the measured data, and the corresponding chart document files are output according to the data processing requirements. At present, the multi-frequency and multi-mode satellite navigation system is developing rapidly, and the research of GNSS tracking stations (such as IGSS-PBO, land state network, etc.) all over the world has a unique resource and development space. With the development of research and technology, GNSS-MR, a new remote sensing tool, is expected to be used in real-time surface environment monitoring (snow, soil moisture, sea level, etc.).
【學(xué)位授予單位】：長安大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：P228.4;P407
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