![]() Column 8 gives how long the command will last. The change rates are given by column 2~7. Command typeĭirectly define the Euler angles change rate and body frame velocity change rate. You can also define GPS visibility of the vehicle for each command.įive command types are supported, as listed below. Indeed, you can add more motion commands to specify the attitude and velocity of the vehicle. There is only one motion command in the above table. Combined with sensor error models, these true values are used to generate gyroscope, accelerometer, magnetometer and GPS output. The simulation will generate true angular velocity, acceleration, magnetic field, position, velocity and attitude according to the commands. Motion commands define how the vehicle moves from its initial state. The initial attitude is represented by Euler angles of ZYX rotation sequence. The initial velocity is specified in the vehicle body frame. The initial position should be given in the LLA (latitude, longitude and altitude) form. Step 2 Create a motion profileĪ motion profile specifies the initial states of the vehicle and motion command that drives the vehicle to move, as shown in the following table. Gps = True to generate GPS data, gps = False not. IMU( accuracy = 'low-accuracy', axis = 9, gps = True)Īxis = 6 to generate only gyro and accelerometer data.Īxis = 9 to generate magnetometer data besides gyro and accelerometer data. IMU( accuracy = imu_err, axis = 6, gps = False) There are three built-in IMU models: 'low-accuracy', 'mid-accuracy' and 'high accuracy'. IMU error model can be specified in two ways: Choose a built-in model Get started Step 1 Define the IMU model Step 1.1 Define the IMU error model This demo shows how to do simulation from logged data files. ![]() This demo shows how to compare resutls of multiple algorithm. This is the algorithm inside Aceinna's INS products.Ī demo of multiple algorithms in a simulation. ![]() This demo shows how to call the shared library. The algorithm is first compiled as a shared library. This is the algorithm inside Aceinna's VG/MTLT products.Ī demo of DMU380 GNSS/INS fusion algorithm. ![]() This demo shows how to generate error plot of interested data.Ī demo of DMU380 dynamic tilt algorithm. The statistics of the INS results of the 1000 simulations are generated.Ī demo of an dynamic inclinometer algorithm based on Mahony's theory. The generated Allan deviation is shown in figures.Ī demo of a simple strapdown system. We provide the following demos to show how to use this tool: file nameĪ demo of generating data, saving generated data to files and plotting (2D/3D)interested data, no user specified algorithm.Ī demo of Allan analysis of gyroscope and accelerometer data. Users choose/set up the sensor model, define the waypoints and provide algorithms, and gnss-ins-sim can generate required data for the algorithms, run the algorithms, plot simulation results, save simulations results, and generate a brief summary. GNSS-INS-SIM is an GNSS/INS simulation project, which generates reference trajectories, IMU sensor output, GPS output, odometer output and magnetometer output.
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