DRV5053EAELPGQ1

Linear, Compass (ICs)

DRV5053EAELPGQ1 is a type of magnetic sensor which consists of an integrated circuit with a built-in analog-to-digital converter. It is designed for applications such as navigation, gestures recognition, and absolute orientation measurements. It operates on two voltage supply ranges from 2.4Volts to 5.8Volts to support a wide array of applications.

Application Field

DRV5053EAELPGQ1 can be used in a variety of applications. The most common would be navigational, gaming, and automotive. DRV5053EAELPGQ1 enables navigation features such as orientation tracking in automotive and robot navigation in consumer products. It can also be used for gaming applications such as gesture recognition and turn-by-turn navigation in virtual reality gaming headsets. In addition, it can be used for automotive applications such as driver assistance systems, steering assistance, and parking assistance.

Working Principle

DRV5053EAELPGQ1 works with magnetometer, Hall-effect technology, and fluxgate magnetometry. It uses a magnetometer to measure the force of a magnetic field in three dimensions. This device then uses Hall-effect technology and fluxgate magnetometry to measure the direction and strength of the magnetic field for precise orientation readings. The Hall-effect technology uses a single current carrying conductor to generate a voltage due to the varying magnetic field in the presence of a different current source. The fluxgate magnetometry uses a coil (toroidal) of wires to measure the magnetic field. The current passing through the wire creates a magnetic field that could be used to measure the components of the magnetic field direction.

DRV5053EAELPGQ1 provides a wide range of features that allow it to adjust itself to various environmental conditions. It offers a wide dynamic range, an adjustable bandwidth filter, as well as a temperature compensation for improved accuracy of the data readings. It also has several advanced features that make it attractive for use in various applications such as gesture recognition, and automotive applications.