calibration/engine/docs/usecase_radar.md

Go to the documentation of this file.

# Copyright (c) 2019-2020, NVIDIA CORPORATION.  All rights reserved.

@page calibration_usecase_radar Radar Self-Calibration

@note SW Release Applicability: This tutorial is applicable to modules in both **NVIDIA DriveWorks** and **NVIDIA DRIVE Software** releases.

## Radar Calibration - Operating Principle

Radar calibration estimates the current sensor orientation (yaw angle) with
respect to the vehicle's coordinate frame. This yaw angle is estimated by first
using the Doppler signal of radar detections to estimate the radar's motion.
Subsequently, the radar motion is matched with vehicle yawrate estimates to estimate
the yaw angle. Calibration measurements require a sufficiently large speed of
driving.

The Doppler motion observed by a radar can also be used to calibrate odometry
speed factors, i.e., a factor which maps measured longitudinal speed to the
actual driven speed. In addition the method can be used to calibration
individual wheel radii by looking for the radius which maps wheel's rotational
velocity to the longitudinal velocity measured by radar. If requested, this
calibration will be performed during straight driving maneuvers.

![Radar yaw (top) and wheel radii / velocity speed factor estimation histograms (bottom), collected over a period of time](self_calib_radar.png)

## Requirements

### Initialization Requirements

- Nominal values on radar calibration
    - Orientation(roll/pitch/yaw): less than 10 degree error
    - Position(x/y/z): x and y are not used for now, z is less than 10 cm error

### Input Requirements

- Sensors: radar calibration requires data from radar and CAN sensors.
- dwVehicleIOState: to perform radar calibration, dwCalibrationEngine has to be fed with `dwVehicleIOState`, with information parsed from received CAN events.
- Assumption: Vehicle performs normal driving maneuvers until calibration convergence.


### Output Requirements

- Corrected yaw value: less than 0.1 degrees
- Time to correction: less than 2 minutes for radar sensor with 15HZ spinning frequency

## Cross-validation KPI

Several hours of data are used to produce a reference calibration value for
cross-validation. Then, short periods of data are evaluated for whether they can
recover the same values. For example, the graph below shows precision/recall
curves of radar self-calibration.
Precision indicates that an accepted calibration is within a fixed precision threshold
from the reference calibration, and recall indicates the ratio of accepted calibrations
in the given amount of time.

![](self_calib_radar_kpi.png)

## Workflow

The following code snippet shows the general structure of a program that performs Radar self-calibration

```{.cpp}
    dwCalibrationEngine_initialize(...);         // depends on sensor from rig configuration module
    dwCalibrationEngine_initializeRadar(...);    // depends on nominal calibration from rig configuration
    dwCalibrationEngine_startCalibration(...);   // runtime calibration dependencies need to be met

    while (true) // main loop
    {
        // code to get CAN measurement
        // code to add vehicle IO state to calibration engine
        dwCalibrationEngine_addVehicleIOState(...);

        // code to get radar motion
        dwRadarDopplerMotion_getMotion(...);

        // feed radar sweep into self-calibration
        dwCalibrationEngine_addRadarDopplerMotion(...);

        // retrieve calibration status
        dwCalibrationStatus status;
        dwCalibrationEngine_getCalibrationStatus(&status, ...);

        // retrieve self-calibrated result
        if (status == DW_CALIBRATION_STATE_ACCEPTED)
        {
            // radar orientation
            dwTransformation3f radar2rig;
            dwCalibrationEngine_getSensorToRigTransformation(&radar2rig, ...);

            // odometry speed factor
            float32_t speedFactor;
            dwCalibrationEngine_getOdometrySpeedFactor(&speedFactor, ...);

            // wheel radius
            for (auto w : {DW_VEHICLE_WHEEL_FRONT_LEFT,
                           DW_VEHICLE_WHEEL_FRONT_RIGHT,
                           DW_VEHICLE_WHEEL_REAR_LEFT,
                           DW_VEHICLE_WHEEL_REAR_RIGHT})
            {
                float32_t radius;
                dwCalibrationEngine_getVehicleWheelRadius(&radius, w, ...);
            }
        }
    }

    dwCalibrationEngine_stopCalibration(...);
```

This workflow is demonstrated in the following sample: @ref dwx_radar_calibration_sample