73 research outputs found

    WiFi-based PCL for monitoring private airfields

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    In this article, the potential exploitation of WiFi-based PCL systems is investigated with reference to a real-world civil application in which these sensors are expected to nicely complement the existing technologies adopted for monitoring purposes, especially when operating against noncooperative targets. In particular, we consider the monitoring application of small private airstrips or airfields. With this terminology, we refer to open areas designated for the takeoff and landing of small aircrafts that, unlike an airport, have generally short and possibly unpaved runways (e.g., grass, dirt, sand, or gravel surfaces) and do not necessarily have terminals. More important, such areas usually are devoid of conventional technologies, equipment, or procedures adopted to guarantee safety and security in large aerodromes.There exist a huge number of small, privately owned, and unlicensed airfields around the world. Private aircraft owners mainly use these “airports” for recreational, single-person, or private flights for small groups and training flight purposes. In addition, residential airparks have proliferated in recent years, especially inthe United States, Canada, and South Africa. A residential airpark, or “fly-in community,” features common airstrips where homes with attached hangars allow owners to taxi from their hangar to a shared runway. In many cases, roads are dual use for both cars and planes.In such scenarios, the possibility to employ low-cost, compact, nonintrusive, and nontransmitting sensors as a way to improve safety and security with limited impact on the airstrips' users would be of great potential interest. To this purpose, WiFi-based passive radar sensors appear to be good candidates [23]. Therefore, we investigate their application against typical operative conditions experienced in the scenarios described earlier. The aim is to assess the capability to detect, localize, and track authorized and unauthorized targets that can be occupying the runway and the surrounding areas

    People counting using multistatic passive WiFi radar with a multi-input deep convolutional neural network

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    Accurately counting numbers people is useful in many applications. Currently, camera-based systems assisted by computer vision and machine learning algorithms represent the state-of-the-art. However, they have limited coverage areas and are prone to blind spots, obscuration by walls, shadowing of individuals in crowds, and rely on optimal positioning and lighting conditions. Moreover, their ability to image people raises ethical and privacy concerns. In this paper we propose a distributed multistatic passive WiFi radar (PWR) consisting of 1 reference and 3 surveillance receivers, that can accurately count up to six test subjects using Doppler frequency shifts and intensity data from measured micro-Doppler (µ-Doppler) spectrograms. To build the person-counting processing model, we employ a multi-input convolutional neural network (MI-CNN). The results demonstrate a 96% counting accuracy for six subjects when data from all three surveillance channels are utilised

    Short-range passive radar for small private airports surveillance

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    This paper investigates the effectiveness of a passive radar for enhancing the security level in small airports and private runways. Specifically WiFi transmissions are parasitically exploited to perform detection and localization of non-cooperative targets that can be occupying the runway and the surrounding areas. Targets of interest include light/ultralight aircrafts, vehicles, people and even animals that may intrude onto the runways either intentionally or accidentally. The experimental results obtained by means of an experimental setup developed at SAPIENZA University of Rome prove the successful applicability of the proposed approach for small airports surveillance. © 2016 EuMA

    A scalable real-time processing chain for radar exploiting illuminators of opportunity

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    Includes bibliographical references.This thesis details the design of a processing chain and system software for a commensal radar system, that is, a radar that makes use of illuminators of opportunity to provide the transmitted waveform. The stages of data acquisition from receiver back-end, direct path interference and clutter suppression, range/Doppler processing and target detection are described and targeted to general purpose commercial off-the-shelf computing hardware. A detailed low level design of such a processing chain for commensal radar which includes both processing stages and processing stage interactions has, to date, not been presented in the Literature. Furthermore, a novel deployment configuration for a networked multi-site FM broadcast band commensal radar system is presented in which the reference and surveillance channels are record at separate locations

    Doppler-only target tracking for a multistatic radar exploiting FM band illuminators of opportunity

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    Includes bibliographical referencesCommensal Radar (CR), defined as a subclass of Passive Radar (PR), is a receive only radar that exploits non-cooperative illuminators of opportunity for target detection, location and subsequent tracking. The objective of this thesis is to evaluate the feasibility of using a Frequency Modulation (FM) Broadcast band CR system as a cost effective solution for Air Traffic Control (ATC). An inherent complication by exploiting FM is the low range resolution due to the low bandwidth of FM radio signals. However, due to typical long integration times associated with CR, the frequency domain resolution is typically very good. As a result, measurements of the target's Doppler shift are highly accurate and could potentially make FM illuminators a viable source for ATC purposes. Accordingly, this thesis aims to obtain a comprehensive understanding of using high resolution Doppler measurements to accurately track the position of a target. This objective have been addressed b by performing a comprehensive mathematical analysis for a Doppler only tracking CR system. The analysis is verified with a tracking simulation, in which the Recursive Gauss Newton Filter (RGNF) is used and lastly, a field experiment was conducted to produce tracking results based on real measurement data. Results demonstrated that Doppler only target tracking from real measurement data is possible, even when the initial target state vector is initialised from real measurement data. A good degree of correlation is achieved between the theoretical, simulated and measured results, hence verifying the theoretical findings of this thesis. Ensuring that the observation matrix is properly conditioned in Doppler only tracking applications is important, as failure to do so results in tracking instability. Factors that influence the conditioning of the observation matrix are; the number of receivers used (assuming the basic observation criteria is met) and the placement of the receivers, keeping in mind the possibility of Doppler correlation in the measurements. The possibility of improving an ill-conditioned observation matrix is also demonstrated. In general, tracking filters, for example the RGNF, typically employ time history information and therefore, a direct comparison to the Cramer Rao Lower Bound (CRLB) is unrealistic and accordingly a new theoretical lower bound, called the Cumulative CRLB was derived that does account for time history measurements. Although the best results for this thesis are achieved by using long integration periods (4 s), the effect of Doppler walk was not compensated for and is an aspect that requires further investigation to potentially further improve on the results obtained in this thesis. As a final conclusion for this thesis; the Doppler only target tracking delivered some encouraging results, however a qualification test in the form of an extensive trial period is next required to motivate Doppler only tracking for ATC purposes

    Indoor target tracking using high doppler resolution passive Wi-Fi radar

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    This paper describes two Doppler only indoor passive Wi-Fi tracking methods based on high Doppler resolution passive radar. Two filters are investigated in this paper, the extended Kalman filter and the sequential importance resampling (SIR) particle filter. Experimental results for these two tracking filters are presented using results from software defined passive Wi-Fi radar using a standard 802.11 access point as an illuminator. The experimental results show that the SIR particle filter performs well using Wi-Fi signals for indoor tracking with a high degree of accuracy. Proposals for simplifying the SIR particle and application to multiple target tracking are also discussed

    Human activity signatures captured under different directions using SISO and MIMO radar systems

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    In this paper, we highlight and resolve the shortcomings of single-input single-output (SISO) millimeter wave (mm-Wave) radar systems for human activity recognition (HAR). A 2 × 2 distributed multiple-input multiple-output (MIMO) radar framework is presented to capture human activity signatures under realistic conditions in indoor environments. We propose to distribute the two pairs of collocated transmitter–receiver antennas in order to illuminate the indoor environment from different perspectives. For the proposed MIMO system, we measure the time-variant (TV) radial velocity distribution and TV mean radial velocity to observe the signatures of human activities. We deploy the Ancortek SDR-KIT 2400T2R4 mm-Wave radar in a SISO as well as a 2 × 2 distributed MIMO configuration. We corroborate the limitations of SISO configurations by recording real human activities in different directions. It is shown that, unlike the SISO radar configuration, the proposed MIMO configuration has the ability to obtain superior human activity signatures for all directions. To signify the importance of the proposed 2 × 2 MIMO radar system, we compared the performance of a SISO radar-based passive step counter with a distributed MIMO radar-based passive step counter. As the proposed 2 × 2 MIMO radar system is able to detect human activity in all directions, it fills a research gap of radio frequency (RF)-based HAR systems.publishedVersio

    An Overview on IEEE 802.11bf: WLAN Sensing

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    With recent advancements, the wireless local area network (WLAN) or wireless fidelity (Wi-Fi) technology has been successfully utilized to realize sensing functionalities such as detection, localization, and recognition. However, the WLANs standards are developed mainly for the purpose of communication, and thus may not be able to meet the stringent requirements for emerging sensing applications. To resolve this issue, a new Task Group (TG), namely IEEE 802.11bf, has been established by the IEEE 802.11 working group, with the objective of creating a new amendment to the WLAN standard to meet advanced sensing requirements while minimizing the effect on communications. This paper provides a comprehensive overview on the up-to-date efforts in the IEEE 802.11bf TG. First, we introduce the definition of the 802.11bf amendment and its formation and standardization timeline. Next, we discuss the WLAN sensing use cases with the corresponding key performance indicator (KPI) requirements. After reviewing previous WLAN sensing research based on communication-oriented WLAN standards, we identify their limitations and underscore the practical need for the new sensing-oriented amendment in 802.11bf. Furthermore, we discuss the WLAN sensing framework and procedure used for measurement acquisition, by considering both sensing at sub-7GHz and directional multi-gigabit (DMG) sensing at 60 GHz, respectively, and address their shared features, similarities, and differences. In addition, we present various candidate technical features for IEEE 802.11bf, including waveform/sequence design, feedback types, as well as quantization and compression techniques. We also describe the methodologies and the channel modeling used by the IEEE 802.11bf TG for evaluation. Finally, we discuss the challenges and future research directions to motivate more research endeavors towards this field in details.Comment: 31 pages, 25 figures, this is a significant updated version of arXiv:2207.0485
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