Comparative Analysis of Velocity Measuring Methods for GNSS Receivers

This paper is a continuation of the author's previous study on methods of velocity measurements of navigation receivers and devoted to their comparative analysis. Each method of measuring velocity has a few parameters. Let us fix all parameters except for one (main) and vary this parameter. The value of each varied parameter corresponds to some noise error of velocity measurements which can be characterized by standard deviation, or SD (cm/s). A dynamic model of GNSS receiver motion determines dynamic errors. Maximal dynamic error (MDE) (cm/s) is of interest in this case. This error depends on "maneuver phase", i.e., a shift of the maneuver start time from the starting point of PLL control period and also the starting point of the secondary processing period. The maximal value of MDE is of interest in these shifts. So, for each value of the varied parameter there is a pair of numbers: SD and MDE. Let us arrange these numbers in plane of the coordinate system: x-axis is MDE, and y-axis is SD. Connect nearest points and obtain a curve which is called an exchange diagram. Since SD and MDE vary within a wide range, the diagrams should be built in logarithmic scale, that is in dB relative to 1 cm/s. Let us call them logarithmic exchange diagrams (LED). Different LED were plotted for tough and soft dynamic scenarios for different methods of velocity measurements including the conventional one frequently discussed in the literature. As a result of the analysis, a method of generating frequency estimates of the input signal and their further filtering using an after-satellite second order tracking filter, and a method based on quasi-optimal estimates of the input signal phase and further after-satellite filtration using the third order tracking filter have been recommended for tougher dynamic conditions. Under more favorable conditions in addition to the two above, a method of generating coordinate increments over one period with further after-coordinate filtration using the second order tracking filter, and a method of generating local coordinates with further after-coordinate filtration using the third order tracking filter have been also recommended. In conclusion, a law of velocity estimate SD variation for one of the best recommended methods was investigated in the process of varying method parameters.