Sylvain Azarian

Automatic Target Recognition for Passive Radar

Air-traffic controllers cannot identify air vehicles flying with a defective or nonexistent transponder. Primary radar does not help, because it cannot classify air vehicles from echoes. Passive radar offers a potential solution, the main difficulty lying in the analysis of the data. We present a novel, automatic object-target recognition system capable of classifying air vehicles observed with passive radar. We describe the testbed we deployed near Orly Airport, and the data it provided over 10 days. A preliminary experiment involving three broad classes, and using a grid of parallel classifiers, gives a promising correct recognition rate of 71%.

Automatic real-time collection of RCS of airplanes in a real bistatic low-frequency configuration using a software defined passive radar based on illuminators of opportunity

In this paper, a novel method of measurement of the real RCS of various airplanes in real conditions, in bistatic mode, and at low frequency is derived. The presence of an airplane is detected by the use of an ADS-B receiver. The RCS of an airplane is derived thanks to the ratio of the power of the received echo signal to the power of the received direct path signal. In practical experiments, a VOR transmitter is used as illuminator of opportunity, and a software-defined radio is used as receiver. The measured RCS will later be used to classify airplanes, in the context of ATR.

Experimental RCS acquisition system: Using software defined radio to build a classification dataset

One of the major issues in testing Automatic Target Recognition (ATR) systems lies in having a sufficient amount of trusted data to be able to estimate efficiency and reliability of the developed algorithms. Generally synthetic data is used because real world data is not easy to obtain or too expensive for academic research. This paper describes an original low-cost automatic acquisition system designed to build a database of RCS acquired with real planes (airliners), in bistatic configuration, at low frequency (VHF). The described system uses ADS-B for target position and a network connected set of Software Defined Radio (SDR) receivers for RF processing. This setup was used to build a RCS database of 1300 commercial airliners in less than two weeks close to Paris-Orly international airport. The web-based graphical user interface was used over this time to remotely monitor the system and make demonstrations.

Dynamically reconfigurable frequency synthesizer for integrated FMCW radar

This paper investigates the design of switched-capacitor filters for reconfigurable frequency synthesizer dedicated to FMCW radar. Simulations mixing electronics level and systems level demonstrates that it is possible to generate a chirp waveform with performances close to the one obtained with an ideal continuous-time filter. This chirp waveform is simulated in a simplified FMCW radar model to evaluate effects of the imperfection on the radar. The motivation of this work is the design of reconfigurable and digitally controlled FMCW source based on free-running VCO.

Modeling and optimization of a dedicated FMCW radar frequency synthesizer

This paper presents the modeling and optimization of a frequency synthesizer dedicated to FMCW radar applications. This frequency synthesizer based on a type-I PLL presents the advantages of a simplified architecture with less potential electronic drawbacks. A methodology to optimize the filter loop is proposed in order to obtain the required smoothed frequency characteristic and correct the VCO distortion.

RETRAM: A network of passive radars to detect and track meteors

When a high speed meteoroid enters atmosphere, its ablation produced by friction with the air molecules ionizes the surrounding gas into a plasma reflecting electromagnetic waves. This phenomenon is well known for radars where the plasma creates a moving target reflecting back the transmitted pulses. This reflection mechanism is also the key for point to point communications where specific wireless systems are designed to use these opportunistic reflectors to open obstructed channels. Most meteoroids fully ablate during their atmospheric entry, from which micrometeorites will eventually reach the ground. For more massive objects which can survive to their atmospheric entry, it is of high interest for scientists and astronomers to collect fallen meteorites. Meteor detection and tracking is the core research work done in the RETRAM group. Conversely to most of the published work on the topic, this project uses passive radar techniques and continuous processing to detect falling objects and to try to estimate their trajectory. Experiment started in the vicinity of Paris, France. This paper describes the underlying physics and architecture of the system, the different illuminators of opportunity used and gives some results for the main showers since 2012.

Revisiting VOR transmitters: MIMO passive radar using legacy infrastructure

VOR is a well-known system used for the routing of aircrafts worldwide. The system is also worth to provide two interesting properties, first to serve as donor to passive radar, second to provide a specific space coding, used for the navigation and that will be precisely explored to localize targets detected in a passive radar mode. VOR is also interesting as it operates in the lower VHF band, a frequency band highly coveted for its counter stealth properties and high detectability of air targets. The paper addresses the potential of this kind of transmitter, considered solely and also in a multistatic configuration.

Recognition of airplanes using merged subspace classifiers

Air-traffic controllers cannot identify airplanes flying with a defective or non-existent transponder. Primary radars do not help since they cannot classify airplanes from echoes. Passive radars offer a potential solution, the main difficulty lying in the analysis of the data. In this paper, we present an automatic target recognition system capable of recognizing airplanes observed with a passive radar. The recognition system relies on the variation of radar cross-section (RCS) of airplanes. Airplanes are recognized by merging the outputs of a grid of parallel classifiers based on subspace methods. The recognition experiments we performed give a correct recognition rate of about 88%.