SkyRadar Blog

In this video we show how the CFAR can help to display targets clearly in the radar scopes (A-Scopes and PPI).

In this article, we shall detail the main results and implementation regarding the processing and classification of RADAR objects using Machine Learning (M.L) techniques such as Hidden Markov Models, Neural Networks or others.

In what follows we will present examples of Deep Learning networks and detail their various designs. It is a detailed tutorial, written for students and engineers who want to acquire a profound understanding of the subject.

In this tutorial, we will have a detailed look at one of the most powerful classes of machine learning and Artificial Intelligence algorithms that exists: the Bayesian Classifiers.

In this short video blog we compare a fixed threshold with the more versatile C-FAR algorithm.

In the first part of this series, we introduced the general concepts needed for understanding the Hidden Markov Models Classifiers. Namely: Bayesian Logic, The concept of Bayesian Classifiers and Bayesian networks. All these notions are now grouped to form a new type of classifier which can accurately model and classify time-series data such as the RADAR data.

In this article we will explore a very special class of classifiers, the Hidden Markov Model Classifiers (HMMs). They are mainly a statistical and probabilistic model but they have found their entry in the world of Machine Learning since they can be trained and classify data.