32 1 Vol 32 1 2011 1 Journal of Harbin Engineering University Jan 2011 doi 10 3969 /j issn 1006-7043 2011 01 016 GNSS SOC 100029 GNSS GDOP 80% 70% 967 1 A 1006-7043 2011 01-0085-05 A satellite selection algorithm in complicated GNSS signal environments CHEN Mohan ZHENG Rui WANG Yun CHEN Jie Institute of Microelectronics Chinese Academy of Sciences Beijing 100029 China Abstract An efficient satellite selection algorithm was proposed for a global navigation satellite system GNSS in complicated signal environments The algorithm used the simplified residual sum of square as the statistic indicator and was able to reflect the pseudorange measurement error of a single satellite An operational approach was also proposed to choose a satellite combination for positioning by detecting and excluding single or multiple false measurements based on the proposed indicator Tests demonstrate that the proposed algorithm is able to significantly reduce possibility of positioning errors in complicated environments compared with the conventional geometric dilution of precision GDOP method The availability of the proposed algorithm is up to 80% on average in static tests and 70% in dynamic tests Keywords GNSS complicated signal environment satellite selection pseudorange error carrier-to-noise density ratio GNSS GDOP GNSS global navigation satellite system 1-3 4 GDOP 5-6 7 GNSS 2010-09-21 863 2009AA011700 1983- E-mail momohanchen@ gmail com 1963- GDOP RAIM receiver autonomous integrety monitoring RAIM
86 32 8 ΔX^ = H T H -1 H T Δρ 3 GNSS 1 2 5 9-11 ΔX GNSS W = X^ - X = ΔX^ - ΔX = H T H -1 H T ε 4 ε 8 0 σ 2 N 0 σ 2 FPGA 8 GPS i 0 ε i ~ N b i σ 2 GPS UERE 8 80% 70% b i GDOP 1 A = H T H - 1 H T A i A i 1 1 x u y u z u Err p = 槡 W 2 x + W 2 y + W 2 z = 槡 A 2 1i + A 2 2i + A 2 3i b i t u 4 6 A 2 1i A 2 2i A 2 3i A i 1 2 ρ j = s j - u + ct u 1 3 ρ j 1 2 n n H s 槡 A 2 1i + A 2 2i + A 2 3i ECEF s ECEF c t u 1 3 1 8 GNSS ΔX Δρ = HΔX + ε 2 2 Δρ Δρ = Δρ 1 Δρ 2 Δρ n n 1 ω = Δρ - H H T H -1 H T Δρ = a x1 a y2 a z3 1 a x2 a y2 a z2 1 H = n 4 a xn a yn a zn 1 ΔX = Δx u Δy u Δz u - cδt u T 4 1 4 3 ε n 1 ΔX W = W x W y W z W t T = H T H -1 0 b i 0 T = A i b i 5 I - H H T H -1 H T Δρ = I - H H T H -1 H T HΔX + ε = I - H H T H -1 H T ε 7 4 ω' = I - H' H' T H' -1 H' T ε' 8
1 GNSS 87 S = I - H' H' T H' -1 H' T 9 Δρ' = Δρ max5 Δρ max6 Δρ maxn n - 4 1 SISS 6 i i = 1 2 n - 4 - j 1 Δρ H' = a xmax5 a ymax5 a zmaxx5 1 a xmaxn a ymaxn a zmaxn 1 H n - 4 4 4 3 n - 4 - j 1 + 1 - j 2 + 1 - H ε' - j m + 1 = 0 m n - 4 n - 4 1 ε SISS statistic indicator of satellite selection SISS = 槡 ω T ω 10 ε i b i SISS SISS = 槡 ε' T Sε' = 槡 Sii b i 11 S ii S i i SISS 6 SISS 1 4 0 Fig 1 Flow chart of satellite selection method proposed σ 2 N 0 σ 2 SISS 1 + C 1 n - 4 + C 1 n - 5 + + C 1 1 0 n 3-2n 2 + 32n - 96 FLOPS 1 7 Ns = 5 k = 5 1 GDOP 4 1 FLOPS Table 1 Computation load comparison for different n 2 n - 4 1 4 SISS 5 i i = 1 2 3 2 j 1 j 1 = 0 1 n - 4 - j 1 + 1 2 SISS 5 min n - 4 n - 4 6 960 1 150 7 080 SISS 5 max > N SISS 5 min N 7 2 611 3 150 SISS 5 max 8 5 984 8 400 20 370 49 280 SISS 5 min 9 12 144 18 900 105 588 10 22 528 37 800 206 640 + 1 SISS 6 max > N SISS 6 min N SISS 6 min SISS 6 min 1 n GDOP
88 32 2 2 1 GPS ARM9 GPS ARM RS232 PC Matlab 2 Fig 2 Availability for different range errors 2 2 2 2 1 2 2 2 GPS GNSS GNSS Sprint R 2008 10 15 STR4500GPS 24 h 10 000 s 50 ~ 200 m 8 3 WGS - 84 4 3 GoogleEarth 4 063 656 11-255 466 33 4 892 925 42 10 000 s 46 04% 8 067 80 67% 1 933 4 2 2 43 44 m 3 6 47 m Fig 3 Position estimates using different algorithmspart of the route 2 Table 2 Position errors in static tests 1 000 s 63 20 m 46 /m X 51 60 42 90 5 66 73 01% 17 Y 30 94 26 70 3 88 Z 57 00 47 28 8 92 3-D 43 44 36 30 6 47
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