PvaRadarCFARParamsRec#

Defined in public/src/operator/include/PvaOperatorTypes.h

struct PvaRadarCFARParamsRec#

Parameters for the PVA Radar CFAR (Constant False Alarm Rate) operator.

Configures the 2-D CFAR detection algorithm, including training and guard cell counts, detection thresholds, padding modes, and optional peak grouping.

Public Members

int32_t numHorTrain#

Number of horizontal training cells for CFAR algorithm (range: 0 < numHorGuard < numHorTrain <= (Width-1)/2) Constraint: 0 <= numHorGuard < numHorTrain < 256 Constraint: 1 <= numHorTrain + numHorGuard < 256 Training cells are used to estimate the noise floor in the horizontal direction.

int32_t numHorGuard#

Number of horizontal guard cells for CFAR algorithm (range: 0 <= numHorGuard < numHorTrain) Constraint: 0 <= numHorGuard < numHorTrain < 256 Guard cells protect the cell under test from target energy leakage in horizontal direction.

int32_t numVerTrain#

Number of vertical training cells for CFAR algorithm (range: 0 < numVerGuard < numVerTrain <= (Height-1)/2) Constraint: 0 <= numVerGuard < numVerTrain < 256 Constraint: 1 <= numVerTrain + numVerGuard < 256 Training cells are used to estimate the noise floor in the vertical direction.

int32_t numVerGuard#

Number of vertical guard cells for CFAR algorithm (range: 0 <= numVerGuard < numVerTrain) Constraint: 0 <= numVerGuard < numVerTrain < 256 Guard cells protect the cell under test from target energy leakage in vertical direction.

PvaRadarCFARHorizontalThreshold horizontalThreshold#

Horizontal CFAR threshold specification.

See also

PvaRadarCFARHorizontalThreshold

float verticalThresholdFactor#

CFAR vertical threshold multiplier Controls detection sensitivity - higher values increase detection threshold detectionThreshold = noiseEstimate * thresholdFactor noiseEstimate is the noise estimate in the vertical direction.

bool isHorizontalCyclicPadding#

Controls padding mode for horizontal dimension during CFAR processing.

When enabled (true):

  • Uses cyclic padding, Uses the training cells from the opposite edge for boundary training cells.

  • Recommended when horizontal data exhibits periodic/cyclic characteristics or when background noise and clutter properties are assumed to be consistent across edges.

When disabled (false):

  • Uses available neighbouring pixels for noise estimation at boundaries.

  • Training cells beyond image boundaries are not included in noise estimation.

  • Recommended when the signal represents an event that is known to start and end within the collected data window, with a genuinely zero-level background outside that window.

bool isVerticalCyclicPadding#

Controls padding mode for vertical dimension during CFAR processing.

When enabled (true):

  • Uses cyclic padding, Uses the training cells from the opposite edge for boundary training cells.

  • Recommended when vertical data exhibits periodic/cyclic characteristics or when background noise and clutter properties are assumed to be consistent across edges.

When disabled (false):

  • Uses available neighbouring pixels for noise estimation at boundaries.

  • Training cells beyond image boundaries are not included in noise estimation.

  • Recommended when the signal represents an event that is known to start and end within the collected data window, with a genuinely zero-level background outside that window.

bool enablePeakGrouping#

Enables peak grouping algorithm for target detection refinement When enabled, the algorithm filters detections to retain only local maxima by comparing each detection against its immediate horizontal and vertical neighbors.