Detection Probability Evaluator

class DetectionProbEvaluator(radar)[source]

Bases: Evaluator, Serializable

Estimates the probability of detection for a given radar detector.

Assumes a successful detection if the Radar's reception contains a non-empty point cloud. This is the case if the configured RadarDetector made a positive decision for any bin within the processed RadarCube.

A minimal example within the context of a Simulation evaluating the probability of detection for a single radar target illuminated by an FMCW radar would be:

 1from hermespy.radar import Radar, FMCW,  ThresholdDetector, DetectionProbEvaluator
 2from hermespy.simulation import Simulation
 3from hermespy.channel import SingleTargetRadarChannel
 4
 5# Create a new simulated scenario featuring a single device
 6simulation = Simulation()
 7device = simulation.new_device(carrier_frequency=60e9)
 8
 9# Configure the device to transmit and reveive radar waveforms
10radar = Radar(device=device)
11radar.waveform = FMCW()
12radar.detector = ThresholdDetector(.02, normalize=False)
13
14# Create a new radar channel with a single illuminated target
15target = SingleTargetRadarChannel(1, 1., attenuate=True)
16simulation.scenario.set_channel(device, device, target)
17
18# Create a new detection probability evaluator
19simulation.add_evaluator(DetectionProbEvaluator(radar))
20
21# Sweep over the target's RCS during the simulation
22simulation.new_dimension('radar_cross_section', [1, .8, .6, .4, .2, .1, 0], target)
23
24# Run the simulation
25result = simulation.run()
Parameters:

radar (Radar) – Radar detector to be evaluated.

evaluate()[source]

Evaluate the state of an investigated object.

Implements the process of extracting an arbitrary performance indicator, represented by the returned Artifact \(X_m\).

Returns: Artifact \(X_m\) resulting from the evaluation.

Return type:

DetectionProbabilityEvaluation

generate_result(grid, artifacts)[source]

Generates an evaluation result from the artifacts collected over the whole simulation grid.

Parameters:

  • grid (Sequence[GridDimension]) – The Simulation grid.

  • artifacts (np.ndarray) – Numpy object array whose dimensions represent grid dimensions.

Return type:

ScalarEvaluationResult

Returns:

The evaluation result.

property abbreviation: str

Short string representation of this evaluator.

Used as a label for console output and plot axes annotations.

property radar: Radar

Radar detector to be evaluated.

property title: str

Long string representation of this evaluator.

Used as plot title.

class DetectionProbabilityEvaluation(evaluation)[source]

Bases: EvaluationTemplate[bool, ScatterVisualization]

Evaluation of the probability of detection for a radar detector.

Represents a boolean indicator of whether a target was detected or not. Generated by the DetectionProbEvaluator’s evaluate() method.

Parameters:

evaluation (ET) – The represented evaluation.

artifact()[source]

Generate an artifact from this evaluation.

Returns: The evaluation artifact.

Return type:

DetectionProbArtifact

class DetectionProbArtifact(artifact)[source]

Bases: ArtifactTemplate[bool]

Artifacto of the probability of detection for a radar detector.

Represents a boolean indicator of whether a target was detected or not. Generated by the DetectionProbabilityEvaluation’s artifact() method.

Parameters:

artifact (AT) – Artifact value.