Title: P3399 Standard for Performance Metrics for Automotive Synthetic Aperture Radar (SAR)
Scope: This standard establishes performance metrics to assess the quality of different imaging techniques applied to automotive synthetic aperture radar (SAR).
This standard provides:
- Guidelines on the type of hardware that can be used and the performance requirements (number of Multiple-Input-Multiple-Output (MIMO) antennas, minimum Pulse Repetition Frequency (PRF), antenna beamwidth, throughput, transmit and receive gains, Effective Isotropic Radiated Power (EIRP), etc.,
- Guidelines on the installation geometries (front looking vs side looking vs corner),
- The computational steps for different focusing algorithms such as the Time Domain Back Projection (TDBP), Fast Factorized Back Projection (FFBP), or focusing schemes such as the Three-Dimensional-Two-Dimensional (3D2D) algorithm,
- The computational steps for different autofocusing algorithms such as hyperbolic summation, Kirchoff, phase-shift, and frequency-wavenumber (Stolt) migration, back-projection, and deep learning techniques,
- Metrics that describe the performance of focusing algorithms including resolution along the delay and cross-range dimensions, integrated sidelobe ratio, and signal to clutter ratio,
- Computational metrics for both the focusing and autofocusing algorithms, such as arithmetic complexity, latency, and throughput,
- A framework for predicting the effects of different waveform modulations and ambiguity functions,
- A framework for assessing the impact of platform position uncertainty on the focusing performance metrics, providing also requirements for the Navigation Units in terms of accuracy of the trajectory in order to properly focus an image,
- Uncertainties and confidence intervals for each measured quantity that can be used to assess the quality of calibration routines,
- A metrologically traceable and unbroken chain of calibrations that relates the final measurements to a standard reference,
- A description of the uncertainties due to systematic (bias) errors versus random measurement errors.