Method and system used for acquiring spatial attitude data

Abstract

The invention relates to a method and a system used for acquiring spatial attitude data. The method comprises the steps that: ADC readings of a sensor on a mobile device are acquired; errors in the ADC readings are eliminated, and the ADC readings are converted into physical quantity data; and physical quantity data of a plurality of sensors are integrated, such that a current spatial attitude data of the mobile device is obtained. According to the invention, ADC readings of the sensors can be processed in an operation system of the mobile device, such that precise mobile device spatial attitude information can be acquired and can be provided for upper applications. Therefore, the threshold for developing advanced spatial positioning applications on the mobile device is lowered, burdens on application developers are reduced, and hardware performance of the sensor on the mobile device can be developed to a maximal extent.

Description

technical field [0001] The invention relates to a method and system for acquiring space attitude data. Background technique [0002] With the reduction of mobile device configuration costs, more and more mobile devices such as mobile phones and tablets are equipped with gravity sensors, gyroscopes, electronic compass and GPS navigators at the same time. The spatial attitude data such as the angular velocity of the device on the X-Y-Z axis, the current roll angle (Roll), pitch angle (Pitch) and azimuth angle (Yaw) of the device become possible, and the obtained spatial attitude data of the mobile device can realize various advanced LBS (Location Based Service location-based services) and augmented reality applications, such as indoor positioning, panoramic photography, and virtual star observation, thereby improving the practicality and fun of mobile devices. In addition, mobile device applications can also use mobile devices to load The gyroscope, gravity sensor, and electr...

AI Technical Summary

Problems solved by technology

[0003] Since the MEMS (Micro-Electro-Mechanical Systems, Micro-Electro-Mechanical Systems) sensors used in mobile devices have various errors, such as temperature drift and zero-point drift, the readings of a single sensor are also easily affected by the external environment, resulting in a difference from the actual value. Large offset, for example, when the mobile device is moving, the current gravity field direction cannot be obtained from the readings of the gravity acceleration sensor, and the current azimuth angle information cannot be obtained from the electronic compass when there is magnetic field interference around

If the raw data of such sensors are directly used, it is impossible to achieve more advanced and accurate positioning applications. At present, the technology of data fusion and attitude estimation based on MEMS sensors has been relatively mature, and is widely used in AHRS systems (attitude heading reference system) However, since related sensors have only been popularized in mobile devices in recent years, existing mobile operating systems such as iOS and Android still directly provide raw sensor data to applications without performing additional data fusion operations , in order to obtain the final required attitude information, application developers need to write their own data fusion algorithms for calculation, and the sensor data often contains interference data, which undoubtedly increases the burden on application developers. Writing and implementing such processing algorithms improves This increases the development threshold of related applications and increases the development cycle. In addition, writing fusion algorithms requires certain professional knowledge, which undoubtedly raises the threshold for obtaining accurate attitude data on mobile devices, hindering the wide application of sensors on mobile devices.

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