Measurement of electromagnetic spectral properties

A radar system comprising one or more processors and one or more storage devices storing instructions that when executed by the one or more processors cause the one or more processors to perform operations comprising:

• generating a series of frequency-modulated chirps i) having respective frequencies across a frequency range across a same frequency range and ii) directed toward a location of a same object in an airfield, each frequency-modulated chirp from the series of frequency-modulated chirps having a different respective portion of frequencies from the same frequency range than another respective portion of frequencies for another frequency-modulated chirp in the series of frequency-modulated chirps;
• receiving a series of reflections reflected from the same object and that correspond to a plurality of frequency-modulated chirps in the series of frequency-modulated chirps;
• generating, from the series of reflections across the same frequency range, a two-dimensional frequency-swept spectral signature representing frequency-dependent features of the same object derived from the series of reflections across the same frequency range, wherein the two-dimensional frequency-swept spectral signature is an image comprising a first dimension representing the same frequency range and a second dimension representing powers of the series of reflections measured at the respective frequencies across the same frequency range;
• and
• providing the two-dimensional frequency-swept spectral signature of the same object as input to a machine learning classifier that is trained to predict characteristics of objects from frequency-swept spectral signatures;
• and
• receiving, from the machine learning classifier, an output representing a predicted classification of the same object as airfield debris or not airfield debris.

A non-transitory computer storage medium encoded with instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

• generating a series of frequency-modulated chirps i) having respective frequencies across a same frequency range and ii) directed toward a location of a same object in an airfield, each frequency-modulated chirp from the series of frequency-modulated chirps having a different respective portion of frequencies from the same frequency range than another respective portion of frequencies for another frequency-modulated chirp in the series of frequency-modulated chirps;
• receiving a series of reflections reflected from the same object and that correspond to a plurality of frequency-modulated chirps in the series of frequency-modulated chirps;
• generating, from the series of reflections across the same frequency range, a two-dimensional frequency-swept spectral signature representing frequency-dependent features of the same object derived from the series of reflections across the same frequency range, wherein the two-dimensional frequency-swept spectral signature is an image comprising a first dimension representing the same frequency range and a second dimension representing powers of the series of reflections measured at the respective frequencies across the same frequency range;
• and
• providing the two-dimensional frequency-swept spectral signature of the same object as input to a machine learning classifier that is trained to predict characteristics of objects from frequency-swept spectral signatures;
• and
• receiving, from the machine learning classifier, an output representing a predicted classification of the same object as airfield debris or not airfield debris.