Calculating the precise geolocation of commercial unmanned aerial vehicles

无人机将通过优化流程和将物流和监控等成本降低到接近零GB的水平，改变所有类型的行业。然而，在商用无人机在我们的城镇安全获得主流和立法接受之前，需要开发能够跟踪和提高无人机能见度的方法。无人机防御旨在证明重新设计我们现有射频传感器网络的硬件/软件的可行性。这项创新将允许我们的网络传感器充当差分GPS参考天线；无人机定位精度可以达到50厘米以下。对于亚马逊、UPS和DHL等公司来说，了解无人机的精确地理位置对于确保：(1)更多的无人机可以飞得更近；(2)精确的包裹投递，例如在一张A4纸上，而不是在某人的花园里；(3)避开关键基础设施，如建筑物和人员；以及(4)采取最短路线到达每个预先计划的点坐标，从而节省电池寿命、时间和金钱。最后，由于我们知道他们的行动空域将受到保护，不会受到不必要的威胁。我们提议的能力将使上述愿景成为商业现实，并允许为后勤行动自由移动合法无人机创造“空中通道”。如果没有我们的解决方案，例如民航局(CAA)可能会限制无人机的使用，可能会损害甚至摧毁这个羽翼未丰的行业。我们提出了一种可行的替代方案来支持该行业并抑制限制性措施。我们的方法将使用最新的遥测方法，并在不久的将来增加人工智能和机器学习能力；实现自动无人机跟踪。我们的技术将为最终用户，如主要城市、机场、监狱和基础设施部门提供地理围栏，以“守卫”他们的领空，使人们能够对商用无人机构成的日益增长的网络威胁保持高度警惕。

Drones are set to transform industries of all types by optimising processes and reducing the cost of e.g. logistics and surveillance to near £zero. However, methods capable of tracking and increasing drone visibility need to be developed before commercial drones gain mainstream and legislative acceptance safely around our towns and cities.Drone Defence herein aim to prove the feasibility of re-engineering the hardware/software of our existing RF sensor network. This innovation will allow our network sensors to act as differential GPS reference antennas; drone positioning accuracies down <50cm could be attainable.For companies like e.g. Amazon, UPS and DHL knowing a drone's precise geolocation is critical to ensure: (1) more drones can fly closer together; (2) pin-point parcel drop-offs e.g. on a sheet of A4 paper rather than in someone's garden; (3) avoid critical infrastructure e.g. buildings and people; and (4) take the shortest route to each preplanned point coordinate, saving battery life, time and money. Finally, with the benefit of knowing their operational airspace is going to be protected and not at risk from unwanted threats.Our proposed capability will allow the above vision to become a commercial reality and allow the creation of "sky ways", for the free movement of legal drones for logistical operations. Without our solution the e.g. Civil Aviation Authority (CAA) could restrict drone usage, possibly damaging if nor destroying this fledgling industry. We propose a viable alternative to support the industry and inhibit restrictive measures.Our approach will use the latest telemetry methodology and in the near future will be augment with artificial intelligence and machine-learning capabilities; enabling autonomous drone tracking.Our technology will offer end-users e.g. major cities, airports, prisons and the infrastructure sector to geofence "guard" their airspace, allowing robust vigilance to the growing network threat posed by commercial drones.