The Indian Regional Navigation Satellite System provides accurate positioning service to the users within and around India,extending up to 1500 km.However,when a receiver encounters a Continuous Wave Interference,its ...The Indian Regional Navigation Satellite System provides accurate positioning service to the users within and around India,extending up to 1500 km.However,when a receiver encounters a Continuous Wave Interference,its positioning accuracy degrades,or sometimes it even fails to work.Wavelet Packet Transform(WPT)is the most widely used technique for anti-jamming in Global Navigation Satellite System receivers.But the conventional method suffers from threshold drifting and employs inflexible thresholding functions.So,to address these issues,an efficient approach using Improved Particle Swarm Optimization based Parametric Wavelet Packet Thresholding(IPSO-PWPT)is proposed.Firstly,a new parameter adaptive thresholding function is constructed.Then,a new form of inertia weight is presented to enhance the performance of PSO.Later,IPSO is used to optimize the key parameters of WPT.Finally,the implementation of the IPSO-PWPT anti-jamming algorithm is discussed.The performance of the proposed technique is evaluated for various performance metrics in four jamming environments.The evaluation results manifest the proposed method’s efficacy compared to the conventional WPT in terms of anti-jamming capability.Also,the results show the ability of the new thresholding function to process various signals effectively.Furthermore,the findings reveal that the improved PSO outperforms the variants of PSO.展开更多
One of the significant features that makes Indian Regional Navigation Satellite System(IRNSS)distinct from most of the other satellite navigation systems is the use of S band signal along with the L-band signals.The f...One of the significant features that makes Indian Regional Navigation Satellite System(IRNSS)distinct from most of the other satellite navigation systems is the use of S band signal along with the L-band signals.The fact that S-band signals experience lesser ionospheric delays and therefore lesser ionospheric gradients than L-band signals is of great advantage,more-so in ionospheric storm conditions.The advantage of using IRNSS S-band signal under ionospheric storm conditions for Ground Based Augmentation System(GBAS)applications is investigated in this paper.The analysis is carried out by computing a GBAS parameter namely sigma-vertical-ionospheric-gradient(σvig)using data from low-latitude stations in Hyderabad,India(17.3850°N,78.4867°E)under both quiet and storm ionospheric conditions and then estimating vertical protection levels(VPLs).It is observed that even in storm conditions,σvig is only 5.08 mm/km with S1 as against 22.80 mm/km due to L5.Also,the VPLs are 0.65 m less than those with L5 and are well within the alert limits.This work carries significance in view of GBAS being planned at several low-latitude airports.展开更多
The Global Positioning System(GPS)is a GNSS constellation,but GNSS is not always GPS.GPS is one of the GNSS constellations used around the world.The GNSS constellations include GPS(US),QZSS(Japan),Beidou/BDS(China),Ga...The Global Positioning System(GPS)is a GNSS constellation,but GNSS is not always GPS.GPS is one of the GNSS constellations used around the world.The GNSS constellations include GPS(US),QZSS(Japan),Beidou/BDS(China),Galileo(EU),and GLONASS(Russia).In 1999,the European Commission(EC)proposed the European Galileo satellite navigation system for the first time.A four-phase development was proposed,including public and private sector finance.Galileo was intended for both civilian and government use,and is managed and controlled by civil authorities.Galileo is made up of 30 satellites,a number of globally distributed ground stations,and a ground control and monitoring system,all of which are extremely similar to the structure,format,and layout of GPS.In this study,we investigate GPS/GLONASS/Galileo/Beidou/IRNSS/QZSS Navigation Satellite System integration algorithm for long baselines ranging from 1500 km to 3000 km in China,Japan and Mongolia.The positioning performance with GPS/GLONASS/Galileo/BDS/IRNSS/QZSS,GPS-only,Galileo-only,GLONASS-only and BDS-only,etc.is compared in terms of the positioning accuracy.An improvement of positioning accuracy over long baselines can be found with GPS/GLONASS/Galileo/BDS/QZSS/IRNSS compared with that of GPS-only and that of BDS-only.The obtained differences of the two baselines(Topcon Magnet Tools Software(Multi-GNSS)-(CSRS-PPP(GPS/GLONASS),(Trimble-RTX(GPS/GLONASS),(AUSPOS(GPS/GLONASS))Online Processing Software)by using GPS/GLONASS/Galileo/BDS/QZSS/IRNSS signals is between 40 cm and 111.5 cm on three days.展开更多
The position accuracy of GNSS is limited by several errors including multipath error.The multipath error is well known as one of the dominant error sources in most of the high-precision GNSS applications,as its fast-c...The position accuracy of GNSS is limited by several errors including multipath error.The multipath error is well known as one of the dominant error sources in most of the high-precision GNSS applications,as its fast-changing and site-dependent nature make it challenging to model and mitigate.The Non-Line-of-Sight(NLOS)signals in combination with the original Line-of-Sight(LOS)signal lead to multipath(MP),which results in erroneous range estimation.To mitigate the effect of multipath,detecting the presence of NLOS/multipath signals plays a vital role.In this paper,GPS and IRNSS signals are considered in simulated multipath environment and in open-sky conditions.A machine learning(ML)approach for classification of LOS/NLOS/multipath is presented in both the environments.In this paper,two classifiers are proposed.The proposed classifiers are trained with signal strength,elevation angle,Doppler shift,delta pseudorange,and pseudorange residuals as attributes.The accuracies of these models are computed and compared and it is found that,among all the algorithms,K-Nearest Neighbors,Decision Tree,and its ensemble functions have demonstrated superior performance.Experimental results are presented using GPS L1,IRNSS L5,and S1 data.A comparative analysis on both the classifiers is also presented.Further,to substantiate these results,another experiment is conducted in a complex real-time dynamic multipath environment and the obtained results are also presented.展开更多
文摘The Indian Regional Navigation Satellite System provides accurate positioning service to the users within and around India,extending up to 1500 km.However,when a receiver encounters a Continuous Wave Interference,its positioning accuracy degrades,or sometimes it even fails to work.Wavelet Packet Transform(WPT)is the most widely used technique for anti-jamming in Global Navigation Satellite System receivers.But the conventional method suffers from threshold drifting and employs inflexible thresholding functions.So,to address these issues,an efficient approach using Improved Particle Swarm Optimization based Parametric Wavelet Packet Thresholding(IPSO-PWPT)is proposed.Firstly,a new parameter adaptive thresholding function is constructed.Then,a new form of inertia weight is presented to enhance the performance of PSO.Later,IPSO is used to optimize the key parameters of WPT.Finally,the implementation of the IPSO-PWPT anti-jamming algorithm is discussed.The performance of the proposed technique is evaluated for various performance metrics in four jamming environments.The evaluation results manifest the proposed method’s efficacy compared to the conventional WPT in terms of anti-jamming capability.Also,the results show the ability of the new thresholding function to process various signals effectively.Furthermore,the findings reveal that the improved PSO outperforms the variants of PSO.
基金the project sponsored by Space Application Centre(SAC),Indian Space Research Organization(ISRO),Ahmedabad,vide sanction letter dated 23 Jan 2017(Project ID.NGP-11),under NAVICGAGAN Utilization programme.
文摘One of the significant features that makes Indian Regional Navigation Satellite System(IRNSS)distinct from most of the other satellite navigation systems is the use of S band signal along with the L-band signals.The fact that S-band signals experience lesser ionospheric delays and therefore lesser ionospheric gradients than L-band signals is of great advantage,more-so in ionospheric storm conditions.The advantage of using IRNSS S-band signal under ionospheric storm conditions for Ground Based Augmentation System(GBAS)applications is investigated in this paper.The analysis is carried out by computing a GBAS parameter namely sigma-vertical-ionospheric-gradient(σvig)using data from low-latitude stations in Hyderabad,India(17.3850°N,78.4867°E)under both quiet and storm ionospheric conditions and then estimating vertical protection levels(VPLs).It is observed that even in storm conditions,σvig is only 5.08 mm/km with S1 as against 22.80 mm/km due to L5.Also,the VPLs are 0.65 m less than those with L5 and are well within the alert limits.This work carries significance in view of GBAS being planned at several low-latitude airports.
文摘The Global Positioning System(GPS)is a GNSS constellation,but GNSS is not always GPS.GPS is one of the GNSS constellations used around the world.The GNSS constellations include GPS(US),QZSS(Japan),Beidou/BDS(China),Galileo(EU),and GLONASS(Russia).In 1999,the European Commission(EC)proposed the European Galileo satellite navigation system for the first time.A four-phase development was proposed,including public and private sector finance.Galileo was intended for both civilian and government use,and is managed and controlled by civil authorities.Galileo is made up of 30 satellites,a number of globally distributed ground stations,and a ground control and monitoring system,all of which are extremely similar to the structure,format,and layout of GPS.In this study,we investigate GPS/GLONASS/Galileo/Beidou/IRNSS/QZSS Navigation Satellite System integration algorithm for long baselines ranging from 1500 km to 3000 km in China,Japan and Mongolia.The positioning performance with GPS/GLONASS/Galileo/BDS/IRNSS/QZSS,GPS-only,Galileo-only,GLONASS-only and BDS-only,etc.is compared in terms of the positioning accuracy.An improvement of positioning accuracy over long baselines can be found with GPS/GLONASS/Galileo/BDS/QZSS/IRNSS compared with that of GPS-only and that of BDS-only.The obtained differences of the two baselines(Topcon Magnet Tools Software(Multi-GNSS)-(CSRS-PPP(GPS/GLONASS),(Trimble-RTX(GPS/GLONASS),(AUSPOS(GPS/GLONASS))Online Processing Software)by using GPS/GLONASS/Galileo/BDS/QZSS/IRNSS signals is between 40 cm and 111.5 cm on three days.
基金sponsored project funded by the Department of Science and Technology(DST),New Delhi,Govt.of India.
文摘The position accuracy of GNSS is limited by several errors including multipath error.The multipath error is well known as one of the dominant error sources in most of the high-precision GNSS applications,as its fast-changing and site-dependent nature make it challenging to model and mitigate.The Non-Line-of-Sight(NLOS)signals in combination with the original Line-of-Sight(LOS)signal lead to multipath(MP),which results in erroneous range estimation.To mitigate the effect of multipath,detecting the presence of NLOS/multipath signals plays a vital role.In this paper,GPS and IRNSS signals are considered in simulated multipath environment and in open-sky conditions.A machine learning(ML)approach for classification of LOS/NLOS/multipath is presented in both the environments.In this paper,two classifiers are proposed.The proposed classifiers are trained with signal strength,elevation angle,Doppler shift,delta pseudorange,and pseudorange residuals as attributes.The accuracies of these models are computed and compared and it is found that,among all the algorithms,K-Nearest Neighbors,Decision Tree,and its ensemble functions have demonstrated superior performance.Experimental results are presented using GPS L1,IRNSS L5,and S1 data.A comparative analysis on both the classifiers is also presented.Further,to substantiate these results,another experiment is conducted in a complex real-time dynamic multipath environment and the obtained results are also presented.
