Deployable sensors for concealed gun detection at a standoff distances.

枪支犯罪在英国和其他许多国家的一些地区都是一个问题。警方有办法发现携带枪支的罪犯，但这通常包括一段时间的监视，以及有针对性的拦截和搜查。目前还没有价格合理的探测器能够遥感一个人是否可能携带枪支。警方确实有扫描仪和传送门，可以安装在机场和主要活动场所等关键地点，以检测携带小金属物品的人，或者使用无害的微波、太赫兹波或极低水平的x射线传送门，以形成隐藏在人身上的枪支的图像。太赫兹和微波可以穿透衣服形成清晰的人体图像，但这项技术产生了道德和技术问题，特别是侵犯隐私。此外，这些并不容易部署，而且在许多情况下仍处于研究阶段。真正需要的是一种便携式装置，能够远距离和离散地探测嫌疑犯是否携带武器，这个拟议的项目旨在开始研制这种装置。在研发过程中，这项研究的目标是首先确定在一系列大气条件下，哪种电磁辐射最能穿透衣服。微波是电磁辐射的一种形式，但也存在其他形式，如光波、红外光、太赫兹波和毫米波，它们穿透织物的能力各不相同。也可以用超声波来探测隐藏在衣服下的金属物体，我们也建议对此进行研究。其中一些形式的电磁辐射会被人体吸收，而另一些则会被反射回来，这取决于确切的波长。我们将以类似于雷达探测船只和飞机的明亮回声的方式寻找枪表面的反射，同时过滤掉来自人体的较低水平反射。枪支并不是唯一可以隐藏在一个人身上的物体，它可以在遥感站点上产生这些明亮的反射。手机、皮革钱包、钢笔和便携式音乐播放器也可以发出可检测的信号。我们的目标是利用枪的独特特征，如枪管和其他腔体来识别反射信号中的独特特征。例如，枪管就像一个共振腔，就像吹拂在乐器上的空气，我们的目标是远程检测这些共振。在调查的第二阶段，我们将利用电磁频谱中最有效的波段，包括无线电频率、微波或其他部分的频谱，再加上超声波，开发一种能有效地远程探测枪支的传感器，并供警方部署。不同的枪可能会从传感器产生不同的反应，但我们将使用类似于自动识别车牌或笔迹的模式识别技术（即神经网络）来学习识别这些特定的反应。这项研究将由一个大学联盟进行，即曼彻斯特城市大学、曼彻斯特大学、哈德斯菲尔德大学和伦敦玛丽女王大学，他们将分别从不同的方面研究这个问题。

Gun crime is a problem in some areas in the UK and many other countries. The police have ways of detecting criminals carrying guns, but this usually involves surveillance over a period of time together with targeted stop and search. There is no affordable detector available that is capable of remotely sensing whether a person is likely to be carrying a gun or not. The police do have scanners and portals that can be installed at key locations such as airports and major event venues to detect people carrying even small metal objects, or portals that use harmless microwaves, THz waves or very low level x-rays to form images of concealed guns on a person. THz and microwaves can form clear body images by penetrating clothing, but moral and technical issues arise from the technology, particularly intrusion into privacy. Also, these are not easily deployable, however, and are still at the research stage in many cases. What is really required is a portable device capable of remotely and discretely detecting whether suspects are carrying weapons and this proposed project aims to commence the development of such a device. During its development, the research will aim to first identify what sort of electromagnetic radiation best penetrates clothing over a range of atmospheric conditions. Microwaves are a form of electromagnetic radiation, but other forms exist such as light, infra-red, Tera-Hertz and millimetre waves and they all differ in their ability to penetrate fabrics. It is also possible to use ultrasound to detect metal objects concealed under clothing and we also propose to investigate this. Some of these forms of electromagnetic radiation get absorbed by the body, whereas others are reflected back depending on the precise wavelength. We will be looking for reflections off the surfaces of the gun in a similar manner to radar detecting the bright echoes from ships and aircraft, whilst filtering out the lower level reflections from the human body. Guns are not the only objects that could be concealed about a person that could give these bright reflections at a remote sensing site. Mobile phones, leather wallets, pens and portable music players could also give detectable signals. We aim to use features unique to a gun, such as gun barrels and other cavities to identify unique signatures in the reflected signals. For example, the gun barrel acts as a resonant cavity rather like air blown over a musical wind instrument, and we aim to detect these resonances remotely. During the second phase of the investigation, we will utilise a mix of the most effective bands in the electromagnetic spectrum, whether that be radio frequencies, microwaves or some other part of the spectrum, together with ultrasound, to develop a sensor that is effective at detecting guns remotely and is deployable by the police. It is possible that different guns will produce different responses from the sensor, but we will use pattern recognition techniques similar to those used in the automatic recognition of number plates or handwriting (i.e. neural networks ) to learn to recognise these particular responses. The research will be undertaken by a consortium of Universities, namely Manchester Metropolitan University, Manchester University, University of Huddersfield and Queen Mary London who will each investigate different aspects of the problem.