Abstract : Reducing the impact of weather changes on the accuracy and stability of barometric altimetry is a problem that needs to be solved in portable navigation systems. To address this, a method for altimetry based on the MS5803 high-precision barometric sensor and local meteorological data is proposed. Starting from the standard barometric altimetry formula, a barometric altimetry equation is derived with any location in the same atmospheric layer as a reference point. Using this equation, with the local meteorological station as the parameter point, and by obtaining the station's near-real-time meteorological data and geographical location via the internet, a more accurate and stable altimeter measurement can be obtained. A prototype barometric altimetry system was constructed using the MS5803-01BA barometric sensor and a laptop computer. Experiments show that at a distance of more than 20 kilometers from the meteorological station, the system's altimeter measurement error is less than 3 meters, and the drift of the fixed-point altimeter measurement value within 13 hours is less than 4 meters.
Keywords : barometric altimeter; weather station; meteorological data; positioning; barometric sensor; MS5803
While the application of GPS-based portable navigation devices is becoming increasingly widespread, GPS's vertical positioning accuracy on the ground is not high and is even affected by urban road conditions, leading to decreased positioning accuracy or even failure to locate, thus limiting its application. Therefore, people are seeking different methods to improve GPS positioning performance in special environments, one of which is to use a barometric altimeter to assist GPS navigation and positioning.
Barometric altimeter measurement is simple and easy to perform, but its test results are significantly affected by weather conditions. In severe cases, the altitude drift of a fixed point can be as much as tens of meters within a day. Therefore, how to improve the accuracy of barometric altimeter measurement has become an urgent problem to be solved in positioning and navigation technology [1-3].
Therefore, this paper proposes an altitude positioning method based on the MS5803-01BA digital barometer and local near-real-time meteorological parameters, and demonstrates the feasibility of this method through theoretical and experimental results. Its accuracy meets the needs of civilian mobile navigation.
1. The principle of barometric altitude testing and its error compensation
1.1 Barometric Altitude Testing Principle
Barometric altimeter measurement is a mature technology. Its working principle involves indirectly calculating the position of the measuring point along the normal direction of the Earth's gravitational potential surface by utilizing the gravity of the air column above it. This altitude is also known as gravitational potential altitude. If geoid anomalies are not considered, the difference between geometric altitude and gravitational potential altitude can be disregarded.
Under standard atmospheric conditions, the gravitational potential height can be calculated using the standard pressure height equation [4].
(1)
Where PH is the air pressure at the measuring point, is the temperature gradient coefficient of this layer, is the standard gravitational acceleration, and and are the lower limits of temperature, air pressure, and altitude of this layer, respectively. Taking the troposphere (H=0-11Km) as an example.
Using equation (1) directly, the height H of the measuring point can be roughly estimated. However, due to the inherent error in the pressure height formula and the influence of other factors, changes in the meteorological environment around the measuring point may cause a large error in the height positioning, with a drift range of up to tens of meters per day. To reduce this error, it is advisable to find a reference point with a known height near the measuring point. By monitoring the temperature and pressure of this reference point, the influence of meteorological environmental changes on the height measurement results can be compensated, thereby improving the accuracy of height positioning.
If the measuring point and the reference point are in the same atmospheric layer, let the height, temperature, and air pressure of the measuring point be and , and let the height, temperature, and air pressure of the reference point be and , then from equation (1) we have
Equations (8) and (9) show that as long as the height of the reference point and related meteorological parameters in the same layer are known, the gravity-based height of the measuring point can be calculated, and the result is independent of the condition of the bottom surface of the atmosphere in that layer. In other words, by using equations (8) and (9), the relevant data of the reference point can be used to compensate for the rational error of barometric altitude measurement.
The difference between the two formulas is that formula (8) uses the reference point temperature, while formula (9) uses the measurement point temperature. If it is standard atmosphere, the results are the same; if it is actual atmosphere, the results will be slightly different.
1.2 Acquisition of meteorological data and location parameters at reference points
The above analysis shows that using real-time meteorological data from adjacent reference points may yield more accurate altitude positioning results. Therefore, obtaining timely meteorological data from reference points becomes a prerequisite for successful barometric altimetry.
Reference {5} introduces a method for acquiring real-time meteorological data from reference points used in the China Regional Positioning System (CAPS). Its core involves collecting data from 1860 automatic meteorological stations in and around China, processing it, and then sending it to end users in the form of a dedicated message. This method is relatively closed and cannot be used by ordinary mobile positioning and navigation systems.
In fact, after years of development, the meteorological system has established a nationwide network of automatic weather stations, with over 2,500 at the national level. The data from these automatic stations is published on professional meteorological websites, allowing anyone to access near-real-time weather data for their region via the internet. For example:
The China Meteorological Administration's China Meteorological Science Data Sharing Service Network not only provides data updates four times a day, but also provides altitude data for the corresponding meteorological stations.
The National Meteorological Center's city weather forecast provides hourly updates of meteorological data for major cities across the country.
Provincial meteorological bureaus can provide more detailed real-time meteorological monitoring data for their respective provinces. For example, the Hubei Provincial Meteorological and Ecological Automatic Monitoring Station Network can provide hourly meteorological data for county-level areas throughout the province.
2. Composition of the barometric alpine system
2.1 Barometric Pressure Sensor
In order to meet the needs of portable navigation and positioning devices, after repeated comparisons, it was decided to select the MS5803-01BA digital barometer manufactured by Precision Electronics of Switzerland {6}.
The MS5803-01BA is a new generation of high-precision barometric pressure sensor module, featuring small size (6.2x6.4mm), high stability, low voltage (1.8~3.6V), and low power consumption (operating current; standby current <). It is equipped with I2C and SPI interfaces, uses a high-performance A/D converter, and can output 24-bit digital pressure and temperature signals with a conversion time as fast as 1ms. The measuring range is 10-1300mbar. The operating temperature is -40~+85℃, and it can be hermetically sealed, making it particularly suitable for outdoor barometric pressure and altitude measurement, with an altitude resolution of up to 0.1m.
The internal structure of the MS5803-01BA is shown in Figure 1. It uses a Wheatstone bridge sensor to detect both absolute pressure and temperature, specifically switched by a multiplexer: the differential mode signal from the bridge is used to detect pressure, and the common mode signal is used to detect temperature. The amplified pressure or temperature signal is converted into a digital value by an ADC, digitally filtered, and stored in D1 and D2 of the digital interface for the host computer to read.
In addition, the factory calibrates each sensor for temperature and pressure, and calculates six 16-bit calibration parameters (C1~C6) which are stored in a 128-bit PROM. Their specific meanings are shown in Figure 3.
The MS5803 is very easy to use. Any computer or microcontroller can connect to it via I2C and SPI buses to acquire and process air pressure and temperature data.
2.2 Prototype System Structure
To facilitate algorithm research, a portable barometric altitude positioning prototype system was constructed using an MS5803 barometric sensor, a laptop computer, and a USB-SPI adapter. The system structure block diagram is shown in Figure 2.
The MS5803 uses an SPI interface and connects directly to the SPI port of the USB-SPI adapter. The GY7502 USB-SPI adapter plugs into the laptop at one end and connects directly to the sensor at the other.
2.3 Main Functions and Flow of the System Software
The laptop's software is divided into two relatively independent functional modules: data acquisition and data processing. The former is responsible for data acquisition and storage, while the latter is responsible for data processing and analysis.
The main workflow of the data acquisition module is shown in Figure 3. After starting data acquisition, the system first reads the six calibration parameters C1~C6 stored in the PROM of the MS5803-01BA via the USB-SPI interface. Then, it reads the pressure conversion value D1 and the temperature conversion value D2, calculates the temperature TEMP and the temperature-compensated pressure P, and writes the temperature TEMP and pressure P to a file. If there is no stop signal, it resumes sampling. Otherwise, it ends sampling and waits for processing.
Data processing is mainly done in Excel, and the basic workflow is shown in Figure 4. First, the hourly air pressure and temperature data of the relevant meteorological station and the corresponding air pressure and temperature records of the measuring point are read in. Then, the height of the measuring point is calculated according to the formula (1), formula (8) and formula (9). Finally, the settlement results are statistically analyzed to understand the accuracy and stability of the height.
3. Experiments and Discussion
3.1 Height Positioning Experiment
To test the effectiveness of the altitude positioning method based on local meteorological parameters and barometric pressure sensors, three experiments were conducted.
3.1.1 Measurement of absolute height
Using the Wuhan Meteorological Station (station number: 57494, longitude: 30°37, latitude: 114°08, altitude: 23.1) as a reference point, the altitudes of a set of known elevation control points were measured at a location in Wuhan city, approximately 22.6 km away. The results are shown in Table 1.
3.1.2 Measurement of relative height
In a high-rise building, starting from the 22nd floor, the air pressure and temperature at the windowsills of each floor were measured and recorded along the fire escape route. Finally, the height of each floor was calculated based on the air pressure and temperature of the ground floor. The experimental curve of the measured height and the actual height of the floors is shown in Figure 5.
The results show that the measured values are very close to the true values, and the coefficient of determination R2 of the linear regression model is greater than 0.999.
3.1.3 Time drift of monitoring height values at fixed locations
Using the Wuhan Meteorological Station as a reference point, the sensor was fixed at a location in the city about 28.5km away. The monitoring system was started and 10 sets of local air pressure and temperature were continuously collected every 10 minutes at 1 second intervals. The hourly air pressure and temperature released by the Wuhan Meteorological Station were also recorded simultaneously.
The height measurement results from 8:00 to 21:00 on April 27, 2011 are shown in Table 2.
The results show that during the 13-hour observation period, the drift range of the height value of the point measured by formulas (8) and (9) is 3.7m, which is significantly lower than the 21.4m of formula (1).
3.2 Discussion of Experimental Results
The experimental data in Tables 1 and 2 show that, compared with Formula (1), Formula (7) and Formula (8) are more accurate and stable in terms of calculation results. By utilizing local meteorological altitude information and near-real-time meteorological data, the accuracy of barometric altimetry can be effectively improved and drift can be reduced.
Note: The height values are the hourly height measurements taken between 8:00 and 21:00 on April 27, 2011.
While using local meteorological data can significantly improve the effectiveness of barometric altitude positioning, the improvement effect of simply using meteorological data is limited by the accuracy and release time of the meteorological station's barometric pressure data.
For example, the atmospheric pressure data resolution at a meteorological station is 0.1 mbar, equivalent to a height resolution of 0.82 m at standard sea level. Furthermore, the hourly data currently available from meteorological stations can vary by more than 1 mbar within one hour, meaning the corresponding height drift could exceed 8.2 m. Therefore, even with high-precision atmospheric pressure sensors, simply using meteorological data makes it difficult to reduce measurement errors to within 1 m.
To further improve the accuracy and stability of barometric altitude positioning, interpolation of meteorological data in space and time can be considered to obtain a more precise and timely benchmark.
4. Conclusion
This paper proposes an altitude positioning method based on a high-precision digital barometer MS5803-01BA and local near-real-time meteorological data, taking into account the needs of mobile navigation. The feasibility of this method is verified through theoretical analysis and experiments, and its accuracy can meet the needs of civilian mobile navigation.
Related products: MS5803, MS5611, MS5607, MS5540, etc.
References:
Authors: Zhao Tiancheng, Rao Hechang
Author's Affiliation: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, Hubei 430079, China
School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, 430074
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