Advancements in the field of robotics together with an increased need for surveillance around critical infrastructure have led to the possibility of utilizing autonomous agents for area monitoring. This paper presents...
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ISBN:
(数字)9798331509231
ISBN:
(纸本)9798331509248
Advancements in the field of robotics together with an increased need for surveillance around critical infrastructure have led to the possibility of utilizing autonomous agents for area monitoring. This paper presents a novel modification to an existing path planning algorithm for autonomous area monitoring, that is more optimized for real-time applications. The proposed Autonomous Surveillance Planner (ASP) discretizes an area into cells and assigns each cell a probability of there being an intruder present based on when the cell was last observed by the agent. The planner then chooses an optimal path through the area by minimizing a cost function describing the probability of not finding an intruder along a path. Since the minimization is computationally costly and scales exponentially with path length, only a short path is computed at a time. This is then repeated, using new information as it becomes available. The ASP was tested both in simulations and during field tests using unmanned ground vehicles with promising results, showcasing that it has potential to be used in a real-world application. ASP was fast enough to be used in real-time and was able to fully cover the intended area. The local planner used for low-level control was computationally costly and would benefit from more computation power or optimization.
It is well known that GNSS receivers are vulnerable to jamming and spoofing attacks, and numerous such incidents have been reported in the last decade all over the world. The notion of participatory sensing, or crowds...
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ISBN:
(纸本)9781665417723
It is well known that GNSS receivers are vulnerable to jamming and spoofing attacks, and numerous such incidents have been reported in the last decade all over the world. The notion of participatory sensing, or crowdsensing, is that a large ensemble of voluntary contributors provides measurements, rather than relying on a dedicated sensing infrastructure. The participatory sensing network under consideration in this work is based on GNSS receivers embedded in, for example, mobile phones. The provided measurements refer to the receiver-reported carrier-to-noise-density ratio (C/N-0) estimates or automatic gain control (AGC) values. In this work, we exploit C/N-0 measurements to locate a GNSS jammer, using multiple receivers in a crowdsourcing manner. We extend a previous jammer position estimator by only including data that is received during parts of the sensing period where jamming is detected by the sensor. In addition, we perform hardware testing for verification and evaluation of the proposed and compared state-of-the-art algorithms. Evaluations are performed using a Samsung S20+ mobile phone as participatory sensor and a Spirent GSS9000 GNSS simulator to generate GNSS and jamming signals. The proposed algorithm is shown to work well when using C/N-0 measurements and outperform the alternative algorithms in the evaluated scenarios, producing a median error of 50 meters when the pathloss exponent is 2. With higher pathloss exponents the error gets higher. The AGC output from the phone was too noisy and needs further processing to be useful for position estimation.
It is well known that GNSS receivers are vulnerable to jamming and spoofing attacks, and numerous such incidents have been reported in the last decade all over the world. The notion of participatory sensing, or crowds...
详细信息
It is well known that GNSS receivers are vulnerable to jamming and spoofing attacks, and numerous such incidents have been reported in the last decade all over the world. The notion of participatory sensing, or crowds...
It is well known that GNSS receivers are vulnerable to jamming and spoofing attacks, and numerous such incidents have been reported in the last decade all over the world. The notion of participatory sensing, or crowds ensing, is that a large ensemble of voluntary contributors provides measurements, rather than relying on a dedicated sensing infrastructure. The participatory sensing network under consideration in this work is based on GNSS receivers embedded in, for example, mobile phones. The provided measurements refer to the receiver-reported carrier-to-noise-density ratio ( $C / N_sensor$ ) estimates or automatic gain control (AGC) values. In this work, we exploit $C / N_sensor$ measurements to locate a GNSS jammer, using multiple receivers in a crowdsourcing manner. We extend a previous jammer position estimator by only including data that is received during parts of the sensing period where jamming is detected by the sensor. In addition, we perform hardware testing for verification and evaluation of the proposed and compared state-of-the-art algorithms. Evaluations are performed using a Samsung S20+ mobile phone as participatory sensor and a Spirent GSS9000 GNSS simulator to generate GNSS and jamming signals. The proposed algorithm is shown to work well when using $C / N_sensor$ measurements and outperform the alternative algorithms in the evaluated scenarios, producing a median error of 50 meters when the pathloss exponent is 2. With higher pathloss exponents the error gets higher. The AGC output from the phone was too noisy and needs further processing to be useful for position estimation.
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