USER_GUIDE.md

AeroIntent Dataset User Guide

AeroIntent is a simulated multimodal dataset for UAV mission intent recognition, built with Unreal Engine 5 and Cosys-AirSim. Each sequence records images, radar returns, navigation data, and annotations while a target UAV performs a particular behavior.

1. What the Dataset Contains

• 3 environments: Park, Landscape (mountainous terrain), and City.
• 15 UAV configurations: three airframe families, Drone, Inspire, and Matrice, each with five payload configurations: no_payload, box, bomb, missile, and gun.
• 5 mission intents and 22 trajectory programs. The benchmark release contains 990 front-view sequences. Additional views collected later are not included in this count.

Intent	Directory	Behavioral Meaning
Transit	transit	Passing through the target region without interacting with the target
Reconnaissance	reconnaissance	Observing the target, for example through orbiting, hovering, or figure-eight flight
Probing	probe	Approaching, probing, and withdrawing, for example through boundary probing or feint attacks
Strike	strike	Converging on the target for a terminal approach
Escape	escape	Leaving the target region, for example through high-speed withdrawal or zigzag evasion

2. Files in a Sequence

A typical directory structure is:

<environment>/<airframe_payload>/<intent>/<trajectory_program>/view_<view>/

For example: park/Drone_no_payload/reconnaissance/orbit_reconnaissance_data_v1_6m/view_front/.

Each view_* directory is a sequence recorded from a specific viewpoint. Each frame identifier corresponds to one saved observation.

Data	File or Directory	Contents and Use
RGB	rgb/*.png	Visible-light images showing the scene, UAV appearance, and behavior
Infrared (IR)	ir/*.png	Simulated infrared images; pixel values are not directly usable as temperatures in degrees Celsius
Depth	depth/*.npz	Raw per-pixel depth in meters; the array key is commonly depth_m
Depth preview	depth_preview/*.png	Depth visualizations for viewing, not a substitute for raw depth in numerical analysis
Echo radar	echo/*.npy	Per-frame radar-return point clouds, which may include both target and background returns
Radar point labels	echo_groundtruth/*.txt	The simulated object name associated with each return point; the target is usually labeled TargetDrone
IMU	imu/imu.csv	The target UAV's angular velocity, accelerometer output, and orientation
GPS	gps/gps.csv	The target UAV's latitude, longitude, and geographic altitude
2D bounding boxes	labels_all.txt	The target UAV's location and size in each image, not its intent class
Timestamps	timestamps.csv	Frame identifiers and times for associating modalities and calculating time intervals
Metadata	meta.json	Viewpoint, sampling frequency, data formats, and trajectory configuration for the sequence
Derived videos	rgb_video.mp4, ir_video.mp4, depth_video.mp4	Videos for browsing and presentation; use the original per-frame files for numerical analysis
Radar status (optional)	echo/echo_status.csv	Per-frame return counts, target-hit counts, and read status; some older sequences do not contain this file

The intent label comes from the parent directory; for example, probe denotes Probing. The configuration directory identifies the airframe and payload, for example Matrice_bomb.

3. Common Data Fields

Timestamps: timestamps.csv

Field	Meaning	Unit
frame_id	Frame identifier within the sequence; for example, 42 corresponds to the filename stem 000042	None
sim_time_ns	Primary timestamp for the saved frame	Nanoseconds (ns)

The target saving rate is usually 10 Hz, but calculate time intervals from the actual timestamps: dt = (next_timestamp - current_timestamp) / 1e9. Subtract the timestamps as 64-bit integers before converting the difference to seconds.

IMU: imu/imu.csv

IMU data describe the target UAV's own motion and orientation, not the motion of the observation platform, GroundStation.

Field	Meaning	Unit
frame_id	Frame identifier used to associate images, timestamps, and other data	None
ang_vel_x, ang_vel_y, ang_vel_z	Angular velocity about the body X, Y, and Z axes, corresponding to roll, pitch, and yaw directions	rad/s
lin_acc_x, lin_acc_y, lin_acc_z	Accelerometer output (specific force) along the body X, Y, and Z axes	m/s^2
ori_w, ori_x, ori_y, ori_z	Quaternion representing UAV orientation, stored in [w, x, y, z] order	None

The body-axis convention is X forward, Y right, and Z down. A quaternion is neither a position nor a set of Euler angles. Accelerometer output must not be integrated directly as world-frame acceleration without accounting for orientation and gravity.

GPS: gps/gps.csv

Field	Meaning	Unit
frame_id	Saved frame identifier	None
lat	Target UAV latitude	Degrees
lon	Target UAV longitude	Degrees
alt	Geographic altitude derived from the simulation's geographic origin; not height above ground	m

GPS can be used to estimate the target's position and trajectory, but latitude and longitude are not metric coordinates. Convert them to a consistent local metric coordinate system before calculating distances or velocities. Adjacent saved frames may contain identical GPS readings.

Echo Radar: echo/*.npy

Each frame typically contains an N x 6 array, where N is the number of return points in that frame. The six columns are ordered as follows:

x, y, z, attenuation, total_distance, reflection_count

Column	Meaning	Unit
x, y, z	Return-point position in the radar sensor's local coordinate frame	m
attenuation	Accumulated attenuation from simulated propagation and reflections	dB
total_distance	Accumulated ray propagation path length; with multiple reflections, this is not the straight-line distance to the target center	m
reflection_count	Number of reflections up to the return point	Count

Labels in the matching echo_groundtruth/*.txt file follow the same point order and can be used to select TargetDrone returns. Return points are not UAV-center positions. The number of points can vary between frames, and a frame may contain no target returns. These six columns do not include Doppler velocity.

When echo_status.csv is present, its most commonly used fields are frame_id (frame identifier), point_count (total point count), target_hit_count (target-return point count), and status (read status). status=ok does not guarantee a target hit; check the target count or point labels as well.

Bounding Boxes: labels_all.txt

The commonly used combined annotation format is:

frame_id xc yc w h

Field	Meaning
frame_id	Identifier of the associated frame
xc, yc	Normalized horizontal and vertical coordinates of the bounding-box center
w, h	Bounding-box width and height as fractions of the image width and height

The image origin is at the top-left corner. For image width W and height H, the box center in pixels is (xc * W, yc * H), and its size is (w * W, h * H).

A line containing only a frame identifier indicates that the frame has no valid target bounding box; it does not necessarily mean that the target is physically absent. This format has no additional class-ID column. Obtain the five-class intent label from the sequence directory.

4. Key Information in meta.json

Field	Meaning for Dataset Users
view	Observation viewpoint, such as front, left, back, or right
frequency_hz	Target saving rate; use timestamps for actual time intervals
drone_vehicle	Recorded target UAV, usually TargetDrone; IMU and GPS data come from this object
camera_vehicle, echo_vehicle	Observation platform carrying the cameras and radar, usually GroundStation
modalities	Enabled modalities; an enabled modality does not guarantee a visible target in every frame or a valid file for every observation
modalities.depth	Depth units, array key, and depth type. DepthPlanar measures depth along the camera's forward axis; DepthPerspective measures distance along each pixel ray
modalities.echo_target_pose_augmentation	Whether target-pose-based radar point augmentation was enabled; if true, not all points can be treated as unaugmented native returns
trajectory_variation.family	Trajectory behavior type, such as orbit reconnaissance
trajectory_variation.context	Sequence identity information, including environment, UAV configuration, and trajectory-program name
trajectory_variation.sampled_params	Configured parameters for this trajectory, such as speed, altitude, and radius; not per-frame measured states

Fields such as bbox_settings, tracking_settings, and writer_options mainly describe how data were collected or files were generated and are generally not needed for routine data loading.

5. Accessing the Dataset

• City data
• Landscape data
• Park data
• AeroIntent paper

See each repository's README for download and shard-reconstruction instructions. The dataset is licensed under CC BY-NC 4.0 for non-commercial use only. Please cite the AeroIntent paper when using the dataset in research.