Methods and Systems for Radar Signal Processing Using Temporal Neural Networks with State-Space Model

A non-transitory processor-readable storage medium having stored thereon data and configurations to control a state machine or cause a processing system to perform operations comprising:

• receiving a raw input signal;
• processing the raw input signal through an encoder path comprising:
• one or more downsample blocks that reduce a temporal resolution of the raw input signal while increasing a channel dimension using learned resampling operations, and
• one or more state space model (SSM) blocks that apply structured state transition operations across a time dimension to generate a bottleneck representation;
• processing the bottleneck representation through a decoder path comprising:
• one or more upsample blocks that increase the temporal resolution while reducing the channel dimension using learned inverse transformations, and
• one or more SSM blocks that apply structured state transition operations to refine a reconstructed signal representation;
• applying skip connections between corresponding encoder and decoder blocks to preserve fine-grained temporal information during reconstruction;
• and
• generating a denoised output signal from the decoder path, the denoised output signal used for real-time enhancement of the raw input signal.

A method for adaptive control of a radar system based on modulation-type identification from digital in-phase and quadrature (I/Q) baseband samples, the method performed by a computing system coupled to a radar receiver and a radar controller, the method comprising:

• receiving, by the computing system, a radar signal comprising digital I/Q baseband samples;
• generating, by the computing system and with a state space model (SSM), an intermediate sequence comprising state space model (SSM) output features that represent temporal dependencies of the digital I/Q baseband samples;
• downsampling, by the computing system, the intermediate sequence by applying a learned downsampling transformation that reduces a sequence length and maps input channels to output channels to form a downsampled intermediate representation;
• generating, by the computing system, a classifier output by providing the downsampled intermediate representation to a classifier;
• identifying, by the computing system and from the classifier output, a modulation type associated with the radar signal;
• and
• updating, by the computing system, the radar system by generating radar-control data that specifies at least one of a threshold setting, a dwell allocation, a waveform schedule, and an assignment of resource priority and by providing the radar-control data to the radar controller.

A method for processing radar signals, the method performed by a computing system having one or more processors and one or more memories, the method comprising:

• receiving a radar signal;
• extracting, using a state space model (SSM), a set of features from the radar signal, the set of features including information associated with phase, frequency, amplitude, and a structure of the radar signal;
• generating a modified radar signal that includes temporal dependencies included in structure of the radar signal;
• downsampling the modified radar signal to generate an intermediate representation of the radar signal;
• providing the intermediate representation of the radar signal to a classifier to generate an output;
• identifying automatically, based on the output, a modulation type associated with the radar signal;
• and
• sending data to adapt a radar operation, based on the identification of the modulation type associated with the radar signal, the radar operation associated with at least one of a threshold setting, a dwell allocation, a waveform schedule, and assignment of resource priority.

A computing device, comprising:

• a memory;
• a processing system coupled to the memory, wherein the processing system includes at least one processor configured to:
• receive a signal;
• extract, using a state space model (SSM) autoencoder, a set of features from the radar signal, the set of features retaining a structure of the radar signal;
• generate a modified radar signal that includes temporal dependencies in the structure of the radar signal;
• downsample the modified radar signal to generate an intermediate representation of the radar signal;
• provide the intermediate representation of the radar signal to a classifier to generate an output;
• identify automatically, based on the output, a modulation type associated with the radar signal;
• and
• send an indication of the identification of the modulation type, the indication configured to induce:
• a radar controller to update a sensing mode or a scheduling decision associated with the radar controller,
• a tracker to initialize, update, confirm, or suppress a target track, or
• a display device to render a label, an alert, a value, or a target icon associated with the signal.

A non-transitory processor-readable storage medium having stored thereon data and configurations to control a state machine or cause a processing system to perform operations comprising:

• receiving a radar signal;
• extracting, using a state space model (SSM), a set of features from the radar signal, the set of features including information associated with phase, frequency, amplitude, and a structure of the radar signal;
• generating a modified radar signal that includes temporal dependencies included in structure of the radar signal;
• downsampling the modified radar signal to generate an intermediate representation of the radar signal;
• providing the intermediate representation of the radar signal to a classifier to generate an output;
• identifying automatically, based on the output, a modulation type associated with the radar signal;
• and
• sending data to adapt a radar operation, based on the identification of the modulation type associated with the radar signal, the radar operation associated with at least one of a threshold setting, a dwell allocation, a waveform schedule, and assignment of resource priority.

A method for analyzing radar signals using a temporal neural network integrated with a state space model, the method comprising:

• receiving in-phase and quadrature baseband samples from a radar receiver;
• processing the received in-phase and quadrature baseband samples with a temporal neural network that includes a state space model to extract one or more latent representations;
• generating an output that classifies a modulation type or identifies a target based on the one or more latent representations;
• and
• adapting, based on the modulation type or target, a radar operation comprising at least one of adjusting a detection threshold, selecting a waveform from a waveform library, updating a dwell allocation, or modifying a resource priority of the computing system.

A non-transitory processor-readable storage medium having stored thereon data and configurations to control a state machine or cause a processing system to perform operations comprising:

• receiving in-phase and quadrature baseband samples from a radar receiver;
• processing the received in-phase and quadrature baseband samples with a temporal neural network that includes a state space model to extract one or more latent representations;
• generating an output that classifies a modulation type or identifies a target based on the one or more latent representations;
• and
• adapting, based on the modulation type or target, a radar operation comprising at least one of adjusting a detection threshold, selecting a waveform from a waveform library, updating a dwell allocation, or modifying a resource priority of the computing system.