Instantaneous GNSS attitude determination: A Monte Carlo sampling approach
Xiucong Sun, Chao Han, Pei Chen
TL;DR
This paper introduces a new real-time GNSS attitude determination method using Monte Carlo sampling and the LAMBDA technique, achieving perfect success rates for ultra-short baselines with single-frequency data.
Contribution
It presents a novel approach combining Monte Carlo sampling with LAMBDA for instantaneous GNSS attitude determination using only single-frequency measurements.
Findings
Achieves 100% success rate for ultra-short baselines.
Employs Monte Carlo sampling to estimate ambiguity probability density functions.
Utilizes a screening-enhanced LAMBDA method for integer ambiguity resolution.
Abstract
A novel instantaneous GNSS ambiguity resolution approach which makes use of only single-frequency carrier phase measurements for ultra-short baseline attitude determination is proposed. The Monte Carlo sampling method is employed to obtain the probability density function of ambiguities from a quaternion-based GNSS-attitude model and the LAMBDA method strengthened with a screening mechanism is then utilized to fix the integer values. Experimental results show that 100% success rate could be achieved for ultra-short baselines.
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