One Size Does Not Fit All: Multi-Scale, Cascaded RNNs for Radar Classification

09/06/2019
by   Dhrubojyoti Roy, et al.
0

Edge sensing with micro-power pulse-Doppler radars is an emergent domain in monitoring and surveillance with several smart city applications. Existing solutions for the clutter versus multi-source radar classification task are limited in terms of either accuracy or efficiency, and in some cases, struggle with a trade-off between false alarms and recall of sources. We find that this problem can be resolved by learning the classifier across multiple time-scales. We propose a multi-scale, cascaded recurrent neural network architecture, MSC-RNN, comprised of an efficient multi-instance learning (MIL) Recurrent Neural Network (RNN) for clutter discrimination at a lower tier, and a more complex RNN classifier for source classification at the upper tier. By controlling the invocation of the upper RNN with the help of the lower tier conditionally, MSC-RNN achieves an overall accuracy of 0.972. Our approach holistically improves the accuracy and per-class recalls over ML models suitable for radar inferencing. Notably, we outperform cross-domain handcrafted feature engineering with time-domain deep feature learning, while also being up to ∼3× more efficient than a competitive solution.

READ FULL TEXT

page 2

page 6

page 9

research
08/11/2017

Deep Recurrent Neural Networks for mapping winter vegetation quality coverage via multi-temporal SAR Sentinel-1

Mapping winter vegetation quality coverage is a challenge problem of rem...
research
06/22/2021

Recurrent Neural Network from Adder's Perspective: Carry-lookahead RNN

The recurrent network architecture is a widely used model in sequence mo...
research
01/05/2019

RNNSecureNet: Recurrent neural networks for Cyber security use-cases

Recurrent neural network (RNN) is an effective neural network in solving...
research
04/19/2020

MuBiNN: Multi-Level Binarized Recurrent Neural Network for EEG signal Classification

Recurrent Neural Networks (RNN) are widely used for learning sequences i...
research
01/17/2019

Visual Reasoning of Feature Attribution with Deep Recurrent Neural Networks

Deep Recurrent Neural Network (RNN) has gained popularity in many sequen...
research
09/05/2017

Multi-Modal Multi-Scale Deep Learning for Large-Scale Image Annotation

Large-scale image annotation is a challenging task in image content anal...
research
11/18/2019

Radar Emitter Classification with Attribute-specific Recurrent Neural Networks

Radar pulse streams exhibit increasingly complex temporal patterns and c...

Please sign up or login with your details

Forgot password? Click here to reset