MODELLING OF GPS SIGNAL LARGE SCALE PROPAGATION CHARACTERISTICS IN URBAN AREAS FOR PRECISE NAVIGATION

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2 Int. J. Elec&Electr.Eng&Telcomm G Sateesh Kumar et al., 2012 Research Paper ISSN Vol. 1, No. 1, October IJEETC. All Rights Reserve MODELLING OF GPS SIGNAL LARGE SCALE PROPAGATION CHARACTERISTICS IN URBAN AREAS FOR PRECISE NAVIGATION G Sasi Bhushana Rao 1, G Sateesh kumar 1* an I Silpa 1 *Corresponing Author: G Sateesh kumar, sateeshkumargula@gmail.com Accurate preiction an moelling of GPS satellite signal propagation characteristics is necessary in all precise navigation solution applications such as aircraft navigations, missile guiance an surveying. The signal propagation characteristics severely affect the quality, availability an continuity of the system. The receive signal strength of a GPS satellite at a given location on or near the earth surface can be preicte by analyzing the propagation characteristics of the channel with an appropriate propagation moel. There are two types of variations that occur in a GPS signal when it is travelling from the satellite to receiver on the earth s surface. They are: large-scale variations an small scale variations. Large-scale variations in a signal are mainly ue to the path loss an shaowing. These variations epen on the istance, carrier frequency an atmospheric conitions. Seconly, the variations those characterize the rapi fluctuation of the receive signal strength over very short travel istance is known as small-scale variations. These are mainly ue to multipath reflections an oppler shift which egraes the quality of the signal receive particularly in urban environments. The large scale propagation characteristics of GPS channel were investigate in this paper. The propagation characteristics of GPS signal was analyze by consiering the factors like carrier frequency an istance between obstacle an receiver. Keywors: GPS, Navigation, Pathloss, Large-scale variations INTRODUCTION Global Positioning System (GPS) is a space base navigation system that provies three imensions position, velocity an time by measuring the istance from the user location to the precise locations of the GPS satellites (Rao, 2010). The accuracy of the compute position epens on the receive signal strength, which may egrae ue to several reasons such as travelling from long istances through vacuum, ense clous, ust particles, ifferent layers of the earth s atmosphere such 1 Department of Electronics & Communication Engineering, Anhra University College of Engineering, Anhra University, Visakhapatnam , Anhra Praesh, Inia. 116

3 as troposphere, ionosphere, protonosphere. In aition the ranom fluctuations in the receive signals ue to ifferent faing phenomena also affect the signal quality an system availability an ultimately a major cause of system outages. The above mentione GPS signal variations can be classifie into two types: i) Large-scale variations an ii) short term variations. The large-scale variations in a signal are mainly ue to pathloss an shaowing. The average value of the signal strength at any point epens on its istance, carrier frequency, type of antennas use, atmospheric conitions an so on, an it may also vary because of shaowing cause by terrain an clutter such as hills, builings, an other obstacles (Branka Vucetic an Jun Du, 1992). This type of signal variation, which is observable over relatively long istances, has a log normal istribution. The secon type of variation is ue to multipath reflections. In urban or ense urban areas, there may not be any irect line-of-sight path between a satellite an a receiver antenna. Instea, the signal may arrive at the GPS receiver over a number of ifferent paths after being reflecte from tall builings, towers an so on. Because the signal receive over each path has a ranom amplitue an phase, the instantaneous value of the composite signal is foun to vary ranomly about a local mean (Xie an Fang, 2000). Whenever, a signal is transmitte from a GPS satellite it follows a multiple number of propagation paths on its way to receiving antenna. These multiple signal paths are ue to the fact that the signal gets reflecte back to the antenna off surrouning objects, incluing the earth s surface. The GPS receiver tracks both the irect an reflecte signal components. LARGE SCALE ANALYSIS Large scale variations are very slow an are calculate over a large area. These variations are generally assume to have log normal istribution. Empirical channel moels have been the best for the analysis of large scale variations. In this paper, the Hata-Okumura Moel is presente which will be use for large scale variation analysis. The path loss equations for urban, sub-urban an rural areas are obtaine for ifferent amounts of obstructions. HATA-OKUMURA MODEL Hata obtaine mathematical expressions by fitting the empirical curves provie by Okumura. In orer to analyze the GPS signals, i.e., the signals transmitte from satellite to GPS receiver, this moel may not be applicable as the istances between the GPS receiver an satellite is aroun 22,000 km an hence the irect line of sight (LOS) path is not possible between satellite an GPS receiver ue to the various factors in the channel like hills, builings an other obstacles. By applying Hata-Okumura moel, the propagation characteristics of GPS signals (L1 an L2) are analyze by consiering the transmitter as one of the obstacle from where the signal is reflecte an the transmitter height is assume to be the height of the obstacle. The following expressions are use for calculating the path loss L (B) for urban, suburban an rural environments. For flat urban areas, 117

4 logf 13.82loght ahm logh log L B where f h t h m = frequency (MHz), t...(1) = height of the obstacle (meters), = height of the GPS receiver antenna (meters), = raio path length. a(h m ) = correction unit for GPS receiver antenna height which epens on the environment. m f a h 1.1log f 0.7 h m 1.56log (2) For example, if the height of one of the obstacle from where the GPS signal is reflecte is 30 m an the receiver antenna height 1.8 m, the moel gives the following path loss at MHz (L1 frequency) for a typical urban area. PL log 10 B, 1Km...(3) Notice that the path loss at 1 km from the obstacle is B. Similarly, the path loss for the same antenna heights at f c = MHz is given by PL log 10 B, 1Km...(4) The pathloss in suburban an open areas is less than that in urban areas. Corrections for etermining pathloss in suburban an rural areas are also etermine by Hata as, For a suburban area, L s L 2 log f (5) For rural areas, f Lr L 4.78 log f 18.33log (6) Accoring to Hata moel, at MHz (L1), the Pathloss in sub-urban area is given as PL su = log 10 Pathloss in rural area is given as PL rural = log 10 Accoring to Hata moel, at MHz (L2) Pathloss in sub-urban area is given as PL su = log 10 Pathloss in rural area is given as PL rural = log 10 The moel is vali for the following range of input parameters: f MHz t m , 30 h 200, 1 h m 10, Km 20 r...(7) 118

5 EFFECT OF VARIOUS FACTORS ON SIGNAL PROPAGATION In orer to esign a propagation moel for the GPS, knowlege about factors contributing to large-scale variations is require. In the following sections, the effect of various factors on the signal power is escribe an appropriate signal propagation moels were esigne. Effect of Distance For the evaluation of the effect of istance on signal power, the terrain is consiere to be quasi-smooth where the average height of surface unulations is 30m or less. The power receive at a given istance from the obstacle varies as per the equation P R k n...(8) where, k is a constant whose value epens on the environment, n lies in the range of 1.5 to 3.5. Effect of Frequency The receive signal level also varies as a function of the frequency, ecreases as the frequency increases. The signal level vary with the frequency accoring to the relation, k PR n...(9) where, k is a constant which f epens on the environment. For example, for a height of the reflecte obstacle h t of m, for a height of the GPS receiver antenna, h m of 3m an when the istance between obstacle an receiver is 20Km, Using Hata moel, the equation for path loss is P L (b) = log 10 f c...(10) where f c is the frequency in MHz. COMPARISON OF SIGNAL VARIATIONS IN URBAN, SUB- URBAN AND RURAL AREAS The propagation of raio waves in built-up areas is strongly influence by the nature of the environment, in particular the size an ensity of builings (Osborne an Yongjun Xie, 1999). The signal strength receive by a GPS receiver woul epen not only on the satellite power, the separation istance between the GPS receiver an the obstacle an carrier frequencies but also on the terrain features. Environmental clutter such as builings, tall structures, trees, lakes, or other boies of water; the with of the streets traverse by the GPS receiver; the angle at which the signal is incient at the receiving antenna; an the irection in which the vehicles travel with respect to the signal propagation also affects the signal strength. In propagation stuies, a qualitative escription of the environment is often employe using the terms such as rural, suburban, urban an ense urban. Dense urban areas are generally efine as being ominate by tall builings, office blocks an other commercial builings, whereas suburban areas comprise resiential houses, garens an parks. The term rural efines open farmlan with sparse builings, woolan an forests. So far, we have only iscusse signal variations in urban areas. Because the effect of the environmental clutter in suburban or rural areas is not as severe, the average 119

6 signal level in these areas is comparatively better. This improvement in the signal levels increases with frequencies, but oes not appear to epen on the istance between satellites an receivers (Hata, 1980). RESULTS Path loss is the important factor in etermining the user position in GPS. The pathloss is epenent on various factors like frequency an istance between the obstacle an the receiver. The variations of pathloss in urban, rural an suburban areas are compare. The analysis has been use for calculating accurate position of GPS receiver. In each case the pathloss increases with increase in istance. This is ue to the fact that in urban or ense urban areas, there may not be any irect line-of-sight path between the satellite an the GPS receiver. Instea, the signal may arrive at a GPS receiver over a number of ifferent paths after being reflecte from tall builings, towers, an so on. Figure 2: Comparison of Pathloss in Urban, Sub Urban an Rural Areas as a Function of Distance for L2 Frequency The comparison of path loss in urban, sub urban an rural areas as a function of istance for L1 an L2 frequencies are shown in Figure 1 an Figure 2. It was observe that maximum pathloss obtaine in urban areas is more compare to the path loss in sub urban areas which in turn greater than in rural areas. Figure 1: Comparison of Pathloss in Urban, Sub-Urban an Rural Areas as a Function of Distance for L1 Frequency Path loss in urban, sub urban an rural areas as a function of istance between obstacle an the GPS receiver for carrier frequencies L1 an L2 are shown in Table 1. From Table 1 it was observe that the path loss increases with the increase in istance between obstacle an the GPS receiver. The comparison of path loss in urban, sub urban an rural areas as a function of carrier frequencies is shown in Figure 3. It was observe that in urban an sub urban areas, the path loss is increasing with frequency while in rural areas, the path loss is ecreasing graually with frequency. 120

7 Table 1: Path loss in urban, sub urban an rural areas as a function of istance between obstacle an receiver for L1 an L2 frequencies Pathloss (B) Urban Areas for Sub-Urban Areas Rural Areas Distance (Km) For Carrier Frequency (Mhz) f c = Mhz Mhz Mhz Mhz Mhz Mhz (L1) (L2) (L1) (L2) (L1) (L2) Figure 3: Comparison of Pathloss in Urban, Sub Urban an Rural Areas as a Function of Carrier Frequencies CONCLUSION In this paper moelling of large scale variations for calculating the path loss was iscusse. In the large scale analysis, the epenency of path loss on carrier frequency an istance between obstacle an receiver was presente in this paper. Path loss increases with the increase in istance between obstacle an receiver an with increase in the carrier frequency. Maximum path loss was obtaine in urban areas which were much more compare to the path loss in sub urban areas an rural areas. This is ue to the fact that the urban areas are generally ominate by tall builings an hence there may not be any 121

8 irect line-of-sight path between the satellite an the GPS receiver. Instea, the signal may arrive at the GPS receiver over a number of ifferent paths after being reflecte from tall builings, towers, an so on. REFERENCES 1. Branka Vucetic an Jun Du (1992), Channel Moeling an Simulation in Satellite Mobile Communication Systems, IEEE Journal on Selecte Areas in Communications, Vol 10. No Hata M (1980), Empirical Formulae for Propagation Loss in Lan Mobile Raio Services, IEEE Trans. Vehic. Tech., Vol. VT-29, No Osborne P an Yongjun Xie (1999), Propagation Characterization of LEO / MEO Satellite Systems at MHz, William University of Texas at Dallas, Rao G S (2010), Global Navigation Satellite Systems, 1 st Eition, Tata McGraw Hill, Inia. 5. Xie Y an Fang Y(2000), A General Statistical Channel Moel for Mobile Satellite Systems, IEEE Trans. Veh. Technol., Vol. 49, pp

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