AULOS: Finmeccanica family of passive sensors

Lallo, A. Di; Farina, A.; Fulcoli, R.; Immediata, S.; Sedehi, M.; Tilli, E.; Timmoneri, L.

doi:10.1109/maes.2017.160037

Cited by 13 publications

(7 citation statements)

References 2 publications

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“…However, if the receive node is able to handle multiple signals (FM, UMTS, DVB-T etc.) [DiL16], [O'Ha12], it can decide in a cognitive manner which channel or set of channels to use for detecting, tracking, and classifying the targets, based on the acquired information on targets themselves and knowledge of source characteristics and transmitter-target-receiver geometry, in the same way as an active radar chooses the transmit waveform on-the-fly, as shown in the previous section.…”

Section: Cognitive Passive Radarsmentioning

confidence: 99%

Cognitive Radars: On the Road to Reality: Progress Thus Far and Possibilities for the Future

Greco

Gini

Stinco

et al. 2018

IEEE Signal Process. Mag.

122

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This paper describes some key ideas and applications of cognitive radars, highlighting the limits and the path forward. Cognitive radars are systems based on the perception-action cycle of cognition that sense the environment, learn from it relevant information about the target and the background, then adapt the radar sensor to optimally satisfy the needs of their mission according to a desired goal. The concept of cognitive radar was introduced originally for active radar only. In this paper we describe how this paradigm can be applied also to passive radar. In particular, we describe (i) cognitive active radars that work in a spectrally dense environment and change the transmitted waveform on-the-fly to avoid interference with the primary user of the channel, such as broadcast or communication systems, (ii) cognitive active radars that adjust transmit waveform parameters to achieve a specified level of target tracking performance, and (iii) cognitive passive radars, that contrary to the active radars cannot directly change the transmitted waveforms, but can instead select the best source of opportunity to improve detection and tracking performance.

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Section: Cognitive Passive Radarsmentioning

confidence: 99%

Cognitive Radars: On the Road to Reality: Progress Thus Far and Possibilities for the Future

Greco

Gini

Stinco

et al. 2018

IEEE Signal Process. Mag.

122

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“…AULOS® is a technologically advanced sensor developed entirely on the basis of a "software defined radar" approach, involving signal sampling directly at carrier frequency using COTS (commercial off the shelf) devices for signal reception and digital processing. The resulting bi-band family offers great flexibility for potential use in a variety of operating conditions, along with enhanced target monitoring distance and position estimate performance, [6].…”

Section: Aulos® Processing Schemementioning

confidence: 99%

“…The exploitation of the FM radio broadcast transmitters represents the best choice for air surveillance applications because they offer high power level and wide coverage. In contrast, the wide horizontal beam and the excellent coverage as well as the wider frequency bandwidth (that allows a range resolution of approximately 20 m) of the DVB-T transmitters make the DVB-T based AULOS system the most attractive solution for maritime surveillance, [6]- [8].…”

Section: Introductionmentioning

confidence: 99%

Eco-friendly dual-band AULOS® passive radar for air and maritime surveillance applications

Martelli

Colone

Cardinali³

2018

2018 IEEE International Conference on Environmental Engineering (EE)

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The last results obtained with the Eco-friendly dualband AULOS® passive radar sensor carried out within the longterm collaboration between Sapienza University of Rome and Leonardo S.p.A. are here reported. Specifically, FM and DVB-T signals are parasitically exploited for air and maritime surveillance applications. A significant effort concerned the development of signal processing techniques to be efficient in both the investigated applications. To this purpose, the recent processing techniques developed by the research group of Sapienza have been applied. We show that the FM-based AULOS is able to detect with great continuity the typical aerial traffic as well as aircrafts with low RCS. In contrast, the DVB-T based sensor can be successfully employed for monitoring vessel of different dimensions both in the proximity of a port that travel during the day. The reported results confirm that the considered sensor can be usefully employed for improving safety and security of public areas, such as airports and harbors, preserving both the landscape integrity and the electromagnetic health of the population.

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“…The research and development in the field of passive radar has been significant over the last two decades. Passive radars have now become an established technology, approaching the stages of commercialization [ 1 , 2 ] and certification [ 3 ]. As a consequence, the radar community is now investigating advanced applications that can benefit from the particular characteristics of a passive radar system.…”

Section: Introductionmentioning

confidence: 99%

Comparison of DVB-T Passive Radar Simulated and Measured Bistatic RCS Values for a Pilatus PC-12 Aircraft

Speirs

Ummenhofer

Schüpbach³

et al. 2022

Sensors

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Passive radar is a technology that has huge potential for airspace monitoring, taking advantage of existing transmissions. However, to predict whether particular targets can be measured in a particular scenario, it is necessary to be able to model the received signal. In this paper, we present the results of a campaign in which a Pilatus PC-12 single-engine aircraft was measured with a passive radar system relying on DVB-T transmission from a single transmitter. We then present our work to simulate the bistatic RCS of the aircraft along its flight track, using both the method of moments and the shooting and bouncing ray solvers, assess the uncertainty in the simulations, and compare against the measurements. We find that our simulated RCS values are useful in predicting whether or not detection occurs. However, we see poor agreement between simulated and measured RCS values where measurements are available, which we attribute primarily to the difficulties in extracting RCS measurements from the data and to unmodeled transmission and received path effects.

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AULOS: Finmeccanica family of passive sensors

Cited by 13 publications

References 2 publications

Cognitive Radars: On the Road to Reality: Progress Thus Far and Possibilities for the Future

Cognitive Radars: On the Road to Reality: Progress Thus Far and Possibilities for the Future

Eco-friendly dual-band AULOS® passive radar for air and maritime surveillance applications

Comparison of DVB-T Passive Radar Simulated and Measured Bistatic RCS Values for a Pilatus PC-12 Aircraft

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