이 예제는 imuSensor System Object를 사용하여 IMU(관성 측정 장치) 측정값을 시뮬레이션하는 방법을 보여줍니다. IMU에는 자이로스코프, 가속도계, 자력계를 포함한 개별 센서의 조합이 포함될 수 있습니다. 각각 gyroparams, accelparams, magparams를 사용하여 개별 센서의 속성을 지정할 수 있습니다.

Magnetometers detect magnetic field strength along a sensor's X,Y and Z axes. Accurate magnetic field measurements are essential for sensor fusion and the determination of heading and orientation.

Generate inertial measurement unit (IMU) readings from a sensor that is mounted on a ground vehicle. Depending on the location of the sensor, the IMU accelerations are different.

Recognize gestures based on a handheld inertial measurement unit (IMU). Gesture recognition is a subfield of the general Human Activity Recognition (HAR) field. In this example, you use quaternion dynamic time warping and clustering to build a template matching algorithm to classify five gestures.

Use the residualgps object function and residual filtering to detect when new sensor measurements may not be consistent with the current filter state.

Global Navigation Satellite System (GNSS) simulation generates receiver position estimates. These receiver position estimates come from GPS and GNSS sensor models as gpsSensor and gnssSensor objects. Monitor the status of the position estimate in the gnssSensor using the dilution of precision outputs and compare the number of satellites available.

Track the position of a ground vehicle using a simulated Global Navigation Satellite System (GNSS) receiver. The satellites are simulated using the satelliteScenario (Satellite Communications Toolbox) object, the satellite signal processing of the receiver are simulated using the lookangles and pseudoranges functions, and the receiver position is estimated with the receiverposition function.

Estimate the position and orientation of a ground vehicle by building a tightly coupled extended Kalman filter and using it to fuse sensor measurements. A tightly coupled filter fuses inertial measurement unit (IMU) readings with raw global navigation satellite system (GNSS) readings. In contrast, a loosely coupled filter fuses IMU readings with filtered GNSS receiver readings.

Generate and fuse IMU sensor data using Simulink®. You can accurately model the behavior of an accelerometer, a gyroscope, and a magnetometer and fuse their outputs to compute orientation.

Parse information from NMEA sentences and use the obtained information to plot the location. In this example, you use the nmeaParser system object available in Navigation Toolbox to:

Estimate the global positioning system (GPS) receiver position using a multi-satellite GPS baseband waveform. You use the receiver independent exchange format (RINEX) and an almanac file to model the GPS constellation and generate a multi-satellite baseband waveform. Simulate the satellite scenario to get relative positions of satellites with respect to the modeled receiver. For this satellite scenario, model the Doppler shift, delay, and received signal power. Based on these calculations, impair the generated baseband signal with Doppler shift, delay, and noise. This example shows how to estimate the simulated receiver position from this impaired GPS baseband signal.