Drone Busters

    

 

     The purpose of Drone Zone is to build a portable radio frequency spectrum analyzer device that can detect the presence of unmanned drone aircraft using signal analysis on nearby radio frequencies. By interfacing an antenna to a processing unit along with a series of other components, our device will capture relative RF activity and present it to the user through a visual display to reveal nearby drone operation.

     The Drone market is expected to grow 34% in 2017 to a $6 billion industry in 2017 and to more than $11.2 billion by 2020 [1]. However, with this vast expansion of the industry comes possible concerns and dangers that arise from the improper use of drones. Privacy concerns are a poplar complaint about drones operating in residential neighborhoods. Recording devices are easily placed on board a drone and can be used to record people inside of their homes with little to no repercussions. Celebrities would be the most concerned with this aspect of drone abuse but even everyday people can fall victim. Air safety is perhaps the leading concern for state and federal law makers. An incident involving a drone flying into an airplane’s engine would have deadly consequences. The FAA says [2] that from January to August 2015 there were 650 pilots that reported drones flying near their aircraft, as opposed to the entire year of 2014 which had only 238 reports. As this trend increases so does the likelihood of a disaster to happen. Drone operation also raises the concern of insurance issues and who is liable in the likelihood of property damage or personal injury due to drones. If a business is susceptible to damage from drones in their airspace, such as airports or windfarms, then insurance rates may increase if they do not have a system for detecting or preventing drone operation in their airspace. The concern of drones being weaponized is also a reality with modern drone technology. Drones could be equipped with bio-chemical weapons or explosives and used for terrorist’s acts. However, the real concern for our immediate community is the threat of drones impeding firefighting tactics from the air. The recent devastation from local fires has left the community with more questions than answers. Many have been wondering why the fire was not combatted from the air as it approached town. While there were a few contributing factors to this reason, one was due to the presence of drones operating near the fire zones.  For this reason, there is a need for a portable system that can detect drones and eventually respond to their presence if deemed necessary.

     There are multiple approaches to methods for drone detection, one being the use of video surveillance. However, video will only cover a short effective area of detection then will lose accuracy. Video also does not allow for detection of drones not in the line of sight of the camera, greatly reducing the applications of use for detection. The company Drone Shield uses an acoustic system to detect drones [5]. However, with audio detection not only is the effective range extremely limited but if you are in a populated area there is far too much noise introduced which further limits the SNR of the audio system. The device must also keep a database of emitted drone noise spectrums for comparison of detected noise patterns. This greatly increases the manufacturing labor cost and would not be effective against any drone not previously recorded and stored into its database. Systems that rely on a radar based detection system such as the Sharpeye Solid State Radar [6] will often miss small drones and allow them to go undetected into an undesired airspace. Radar also becomes ineffective against low flying drones or drones that are behind objects that may block the radar, such as buildings and trees. Thermal drone detection [3] has issues with detection range as well as misidentification at farther distances, much like the dilemmas seen with video drone detection. Radio frequency signal processing is the most effective method for drone detection. The FCC allocates blocks of the RF spectrum for specific industry and application use [4]. This will allow our device to analyze the RF activity on the specifically allocated spectrum bandgap designated for unmanned drone operation. This means we are accurately able to detect the presence of an operating drone even if there is no line of sight to the drone, whether the drone is low or high flying and even if the drone is acoustically drowned out by ambient noises.

 

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References

 

[1] “Newsroom,” Gartner Says Almost 3 Million Personal and Commercial Drones Will Be Shipped in 2017, 09-Feb-2017. [Online]. Available: https://gartner.com/newsroom/id/3602317. [Accessed: 15-Nov-2017].

[2] “Pilot Reports of Close Calls With Drones Soar in 2015,” FAA seal, 13-Aug-2015. [Online]. Available: https://www.faa.gov/news/updates/?newsid=83445. [Accessed: 15-Nov-2017].

[3]  Rohde & Schwarz, et al. “Drone Detection and Location Systems.” Microwave Journal, Microwave Journal, 2017, www.microwavejournal.com/articles/28459.

[4] “United States Frequency Allocations, The Radio Spectrum” U.S. Department of Commerce. https://www.ntia.doc.gov/files/ntia/publications/2003-allochrt.pdf

[5] “Home Index” DroneShield, www.droneshield.com/

[6] “New Orleans, Louisiana, United States,” Kelvin Hughes. [Online]. Available: https://www.kelvinhughes.com/security/uav-drone-detection  [Accessed: 15-Nov-2017].