Patent Publication Number: US-11644535-B2

Title: Deterrent for unmanned aerial systems

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. patent application Ser. No. 17/214,413, filed Mar. 26, 2021, now U.S. Pat. No. 11,378,651; which is a continuation of U.S. patent application Ser. No. 16/876,387, filed May 18, 2020, now U.S. Pat. No. 11,035,929; which is a continuation of U.S. patent application Ser. No. 16/183,935, filed Nov. 8, 2018; now U.S. Pat. No. 10,670,696; which is a continuation of U.S. patent application Ser. No. 15/627,229 filed Jun. 19, 2017; now U.S. Pat. No. 10,156,631; which is a continuation of U.S. patent application Ser. No. 15/368,269 filed Dec. 2, 2016, now U.S. Pat. No. 9,715,009; which is a continuation-in-part of U.S. patent application Ser. No. 14/821,907 filed Aug. 10, 2015, now U.S. Pat. No. 9,689,976; which claims benefit of U.S. Provisional Application No. 62/094,154 filed Dec. 19, 2014. The disclosures of each of these prior applications are incorporated herein in their entirety by reference. 
    
    
     STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT 
     None. 
     FIELD 
     The technology herein relates to reliable detection and interdiction of unmanned aerial systems such as drones. 
     BACKGROUND AND SUMMARY 
     Small Unmanned Aerial Systems (sUAS), weighing less than 20 kg or 55 pounds, which are commonly referred to as “drones”, are commercially available to the general public. Drone—designated as  44  in  FIG.  1 A , thus refers to an unmanned aircraft or ship guided by remote control or onboard computers, allowing for human correction (i.e., semi-autonomous), or autonomous, see also UAV, UAS, sUAS, RPA. While there may be many safe commercial and recreational uses for unmanned aerial systems, recent publicized events tell us that significant hazards exist to commercial and general aviation, public, private and government interests even if a drone is operated without malicious intent. Furthermore, unmanned aerial systems have been used intentionally to violate the privacy of personal, commercial, educational, athletic, entertainment and governmental activities. An unintended consequence of off-the-shelf (OTS) commercially available unmanned aerial systems is the capability to be used in the furtherance of invading privacy, or carrying out terrorist and/or criminal activities. There is a genuine need for an integrated system and method of detecting, tracking, identifying/classifying and deterring the approach of a commercial unmanned aerial system towards a location where personal, public, commercial, educational, athletic, entertainment, governmental and military activities occur and where a commercial unmanned aerial system could potentially be used for invading privacy, or carrying out terrorist and criminal activities within a civilian environment. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    shows an example of non-limiting drone detection, classification and interdiction system. 
         FIG.  1 A  is a schematic representation of the components and function of an example non-limiting integrated detection and countermeasure system for use against small-unmanned aerial systems (sUAS). 
         FIG.  2    is a schematic representation of the deterrent and countermeasure system for use against small unmanned aerial systems (sUAS),  44  of  FIG.  1 A . 
         FIG.  3    is a schematic representation of the Radio Frequency (RF) detection system for use against small unmanned aerial systems (sUAS),  44  of  FIG.  1 A . 
         FIG.  4    is a schematic representation of the Radar detection system and Electro Optical/Infer Red (EO/IR) camera &amp; Laser Range Finder (LRF) system for use against small unmanned aerial systems (sUAS),  44  of  FIG.  1 A . 
         FIG.  5    is a simplified flow-chart showing computational processes and functions that locate, identify/classify, track and deter a small unmanned aerial system (sUAS),  44  of  FIG.  1 A  in an automated manner. 
         FIG.  6    is an example non-limiting process diagram for an embodiment of the sensor fusion processor. 
     
    
    
     DETAILED DESCRIPTION OF EXAMPLE NON-LIMITING EMBODIMENTS 
       FIG.  1    shows an example non-limiting system for detecting, tracking, classifying and interdicting a UAS such as a drone  44 . In the example shown, several different sensors using different technologies are used to detect the target  44 . Such sensors include, in one non-limiting embodiment, a commercial ground based radar  43 ; an optical and/or infrared and/or laser range finder  16 ; an omnidirectional radio frequency (RF) receiving antenna  14 ; and a directional radio frequency (RF) receiving/direction finding antenna  12 . Such equipment can be mounted on separate fixtures such as mobile trailers, or on the same fixture or other structure. The outputs of these sensors are analyzed using a sensor fusion processor (described below) to detect and classify the target  44 , and to determine a level of threat assessment. In some non-limiting embodiments, a human can be in the loop (HiL or “human in the loop”) to render judgment; in other scenarios, the system is entirely automatic enabled by algorithms applying data mining. If the threat assessment level exceeds a certain threshold, the system can automatically deploy interdiction  10  to incapacitate or destroy the target  44 . The system can therefore be instrumental in protecting critical infrastructure such as airports, bridges, power lines, factories, nuclear/power plants, shipping facilities, football stadiums, military installations, large public venues, etc., from being threatened by the target  44 . 
     Example non-limiting embodiments provide a fully integrated multi-phenomenology detection and interdiction solution which leverages the strength of multiple individual sensor systems including but not limited to: Radar, Radio Frequency Direction Finding (DF), Electro Optical and Infra-Red (EO/IR) imagers, and Laser Range Finding (LRF), used to derive necessary location and spectral characteristics of a commercial unmanned aerial system (UAS) or drone. Unique analytic processes and algorithms use the data collected by the sensor suite to identify, classify and specify the specific waveform, pulse width, and frequency to be generated for use by an RF counter-measure, thereby exploiting inherent vulnerabilities within the onboard electronic controls of an object of interest such as a sUAS—designated as  44  in  FIG.  1    small Unmanned Aerial System, usually weighing less than 20 kg or 55 lbs. The highly accurate, narrow beam RF counter-measure transmits the specifically generated RF signal, disrupting and overwhelming the subject unmanned systems control and navigation systems resulting in an airborne unmanned system landing or returning to launch location based on the subject&#39;s onboard processes. 
     Traditionally, air defense has been the purview of the military, not law enforcement or private security forces. However, the advent of affordable and capable sUAS, weighing less than 20 kg or 55 pounds, creates a need to detect and deter unauthorized or hostile use of this technology. Small drone systems present different detection signatures, flight characteristics and profiles, and are not likely to be detected by more conventional radar or deterred by electronic countermeasures, or kinetic systems without the risk of significant collateral damage. Existing UAS countermeasure systems are designed primarily and focus on detecting and destroying larger aircraft such as drones similar to the Iranian Ababil 3, Chinese Sky-09P and the Russian ZALA 421-08 for example. These midsize to large unmanned aerial vehicles are not likely to be used within a domestic, non-combat, environment. Due to their size and flight characteristics, detecting and tracking midsize to large military drones is accomplished with great success using traditional military radar/air defense systems designed to scan the sky. In addition, the military countermeasures used to combat UAS/UAVs against friendly positions consist of lethal offensive systems armed with deadly and destructive munitions such as bullets, artillery, electromagnetic and laser beams. Also integrated in the military countermeasures are powerful RF systems designed to disrupt, jam or spoof the SATNAV (GPS) (satellite navigation/global positioning system) signals needed for aerial navigation. This traditional approach produces a high risk of collateral damage or negative navigation effects on all GPS receivers operating in the area. The system of the non-limiting embodiments(s) resolves these negative or collateral effects by offering a precise and tailored application of the specific RF emission needed to remotely control these small commercial drones without specifically targeting the SATNAV (GPS) signal. 
     Military UAS countermeasures are designed and used in a battlefield or hostile environment. Using a military solution within a civilian or commercial environment would not be suitable or permissible due to the inherent liabilities and government regulations. Furthermore, the use of SATNAV/GPS jamming and spoofing can severely disrupt broad military and civilian activities such as cell phone towers and aviation navigation making it illegal outside of a military operation or combat zone. Another issue with using current military UAS/UAV countermeasures against commercial drones is the military focus on traditional force protection and counter battery missions using battlefield radar systems that are not designed for or capable of detecting slow moving targets that operate at relatively low angles or altitudes above buildings, trees and just above the horizon. Using countermeasure systems that rely only on aircraft detecting radar and GPS jamming/spoofing systems does not provide a viable defensive solution to commercially available sUAS. The full military approach to UAS countermeasure system has several drawbacks with its use in a civilian or commercial environment that includes cost, weight, size, power consumption and collateral effects using high-powered RF jamming or kinetic technologies. This gap between the military and civilian operational environment demands that an integrated, multi-sensor counter sUAS system be developed. The demand for a successful counter sUAS system that detects, tracks, identifies/classifies and deters against commercial drones without causing collateral damage or interference in a civilian environment is growing exponentially and is directly applicable to other unmanned systems employing similar technology. 
     The exemplary non-limiting implementations herein alleviate the problems noted with the military counter UAS systems and provide a novel, efficient and effective integrated detection, tracking, identifying/classifying and countermeasure solution against small unmanned aerial systems (sUAS) operating in a commercial or civilian environment. The implementations herein further offer increased awareness, security, privacy, and protection from the threats involving small unmanned aerial systems/vehicles, (sUAS/UAV) or other similar manned systems—such as ultra-light aircraft, and is applicable to governmental, military, commercial, private, and public concerns. Example embodiments herein provide Counter Unmanned Aerial Systems of Systems (CUASs2) to detect, identify/classify, track and deter or interdict small unmanned aerial vehicles or systems 
     The example non-limiting systems disclosed herein provide an integrated solution providing protection from ground level to several thousand feet above ground level and laterally several miles comprising components using in part: some existing technologies for a new use; multiplexing hardware components designed for this application; development of the integrating sophisticated built-in software algorithms which calculates the exact X, Y, Z (Longitude, Latitude and Altitude) coordinates of the subject sUAS; subject sUAS RF signal analysis to determine the most appropriate RF signal characteristics required to affect the subject sUAS; video/photo analytics to identify/classify sUAS type and threat assessment, precision alignment of high definition electro-optical (EO) sensors and infrared (IR) sensors and image recognition algorithms; a Laser Range Finder (LRF) capable of tracking multiple targets, providing X, Y, Z coordinate data, heads-up display data and a fire-control capability. Such capability allows for operation in a completely autonomous manner or in a supervised manner by providing a system operator, also known as a Human-in-the loop (HiL), a real-time imagery and data to assist in picture compilation and threat assessment as well a visual display of the suspect sUAS location and image, thus, providing positive confirmation that the targeted sUAS/UAV is in violation of airspace authorization, presents a physical threat to an area of concern or has entered a designated protected area. 
     Operating a counter sUAS system within a civilian or commercial environment will mandate precision countermeasures to ensure very minimal to zero collateral damage or exposure to areas surrounding the targeted sUAS. The non-limiting embodiments(s) unique capability is the way it integrates multiple sensors to detect, track, identify/classify and deter sUAS/UAV systems. In addition, the system utilizes three independent sources to acquire the X, Y and Z coordinate data needed to automatically direct and align the automatic antenna alignment system and provide the initial targeting/tracking data to the EO/IR system ( 16 ) and the countermeasure system ( 10 ). The three independent sources are the radar system ( 43 ), the DF system ( 14 ) and the combined EO/IR &amp; LRF system ( 16 ). Combining the independent X, Y, and Z coordinate data of each system will provide a precise 8-digit GPS geo-location/tracking to use in the geo-location, mapping, aiming and tracking systems. It should be noted that the military systems rely only on radar for GPS location when tracking a suspected airborne target or UAV. 
     The example non-limiting technology herein utilizes radar in the X-Band frequency range as one of the sensors to detect, track and classify a commercial sUAS/UAV. The unique application of radar more typically used to detect ground targets allows greater discrimination between the suspect sUAS and the highly cluttered, low altitude environment. Military air defense radars are optimized for much higher altitude and velocity targets utilizing the K and Ka bands. Existing art approaches the technical challenge of sUAS detection like any other aerial target while the non-limiting embodiments(s) described approaches this challenge as if it were a ground target. This fundamentally different approach provides a novel and unique solution for the detection of airborne sUAS or similar signature systems. Due to the high frequency, range, power, and other optimized characteristics, typical applications of aircraft detection radars are more susceptible to distortion when viewing ground-associated objects that is then classified as “Clutter”. 
     The example non-limiting technology herein utilizes a Laser Range Finder (LRF) coupled with an Electrical Optic and Infra-Red (EO/IR) camera system as one of the sensors to detect, track, and identify/classify a commercial sUAS/UAV. The EO/IR &amp; LRF system ( 16 ) receives its initial target data (location) from the radar system ( 43 ). The X, Y and Z coordinate data from the radar aligns the EO/IR camera and LRF towards the suspect sUAS target. The LRF is a comprehensive, multi-purpose targeting system that incorporates the same tracking and fire-control capabilities found in advanced military weapon systems including fighter aircraft, armored vehicles, and precision-guided munitions. The LRF combined with the EO/IR camera system provides the digital display to the system operator, (HIL), that shows the field of view and displays the suspect sUAS target(s) along with vital pieces of data including range-to-target, target velocity, deterrent angle, compass heading, wind velocity and direction, deterrent zone size, countermeasure type, temperature, barometric pressure and time of day. Fire control technology is at the core of the LRF and ensures extreme accuracies at long distances with slow to fast moving sUAS targets. It is what allows the non-limiting embodiments(s) to execute precision countermeasures within a controlled civilian or commercial environment. Fire control systems are basically computers that guide the release of the chosen countermeasure. Once the suspect sUAS is tagged the LRF produces an X, Y and Z data point that is sent to the countermeasure system ( 14 ) for automatic alignment of the destructive or non-destructive deterrent element ( 10 ), (RF, Laser, Impulse, Munitions, etc.). This is a significant advantage over current military systems for providing the necessary steps for increased safety when operating in a civilian/commercial environment. During the time that the suspect sUAS is being viewed through the EO/IR camera system, data mining techniques based on internal and external databases are used to compare the images and heat signatures with known sUAS images and heat signatures for possible type identification/classification and threat assessment. Video/photo analytics are used to determine the type of sUAS and if the suspect sUAS contains a payload. 
     The example non-limiting technology herein utilizes components of the LRF to connect the tracking EO/IR optic with the fire control trigger. Targeting technology lets you designate an exact sUAS target(s) by placing the aligned reticle on the sUAS and then pressing the tag button. When you tag a target, the tracking optic then knows what you want to engage. The optic and trigger collaborate to precisely release your chosen countermeasure. Once the decision has been made to engage the target sUAS, the tracking system then guides the fire control trigger to release the countermeasure at the exact moment needed to affect your target with minimal collateral damage to areas surrounding the target sUAS. The connection between the tracking optic and the fire control trigger contains dozens of microprocessors and electronic, electro-optic, and electro-mechanical components. When the system engages the fire control triggering mechanism, the image is compared to the original selected image, again using processes based on data mining techniques. If the two images are not perfectly aligned with the designated or tagged point, the tracking optic interrupts the triggering signal and prevents transmission of the tailored RF interdiction signal. At the time when the images are aligned and matched, the interrupt is released allowing the transmission of the desired interdiction transmission. As soon the system intersects the designation point, the fire control trigger is released executing a perfectly aimed deterrent countermeasure. This automated fire control system virtually eliminates human error caused by misaiming, mistiming, system movement, vibration or other environmental factors. 
     One example non-limiting technology herein utilizes Radio Frequency (RF) and Direction Finding (DF) technology to detect, and track, identify/classify a commercial sUAS/UAV. The system uses a very sensitive RF receiver scanning the area of interest, in a 360-degree manner, for any RF signal commonly used as the communication link between the operator and the sUAS. Filters within the signal processor eliminate those signatures that are not found within the population of the commercially available sUAS market. Observed signal characteristics are compared to a library or database of modulation, frequency, pulse-width and duration characteristics to identify known commercial sUAS. When an observed signal matches or is statistically similar to an expected sUAS RF signature, the azimuth of the suspect sUAS is passed to the other sensor systems for closer attention. The high gain antenna is also directed to that azimuth further refining the azimuth and elevation of the suspect sUAS. This system sensor element allows the non-limiting embodiments(s) to operate passively when required. 
     The example non-limiting technology herein utilizes a deterrent element to deter, suppress, control or destroy if operated in an applicable environment an unmanned system. Additional deterrent values include the ability of the systems detect function to locate and track low flying airborne threats that are not sUAS/UAV in nature. Any future technology will by matter of physics present a variety of signatures which are observable by the non-limiting embodiments(s) fused set of sensor phenomenology&#39;s, even though they may avoid detection by conventional air defense systems. In addition, should the FAA (Federal Aviation Authority) mandate future transponder identification processes on commercial sUAS/UAV; the non-limiting embodiments(s) RF/DF system is designed to accept state data generated by non-organic sensors and will incorporate this “told-in” data into the target identification process and algorithms. 
     As stated above, the example non-limiting technology herein is designed to accept but does not require; subject sUAS location, classification, or other state data generated by non-organic sensors. The integration of these components via the herein disclosed mechanism, is a novel combination of software and hardware, not related to existing art in purpose, is non-obvious, and provides a useful solution to uninvited, invasive and potentially hazardous commercial sUAS/UAV operations regarding privacy, security, illegal activity and terrorist threats from commercial unmanned aerial vehicles. The individual elements of the non-limiting embodiments(s) are linked via secure internal control networks and can use existing communications infrastructure or dedicated high bandwidth point-to-point communications hardware to operate the entire system remotely or add additional sensors from remote sources. 
     The system of the example non-limiting technology herein provides an integrated multi-sensor system that can be deployed as a “permanent placement” or as a mobile system on land, sea, or air platform. 
     The system of the example non-limiting technology herein may be strategically deployed to monitor the airspace around a protected interest such as a property, place, event or very important person (VIP) offering 360-degree azimuth coverage extending from the receiving antennae of the system out to a lateral distance of about 2 kilometers (6560 feet) and within the lateral boundaries up to an altitude of about 1.5 kilometers (4920 feet) above ground level (AGL). These distances are averaged and may increase through the natural progression when incorporating future technologies and optional embodiments. The area within the detection boundaries is considered to be a designated protected area. A protected area is identified, outlined and overlaid on the system mapping display and can be viewed remotely and monitored by the system operator/HiL. 
     The deterrent system,  102 , transmitted RF frequency power is variable based on range and observed effect on the subject sUAS control system. The highly focused RF beam minimizes collateral effects on non-target receivers. 
     A multi-sensor system for providing integrated detection, tracking, identify/classification and countermeasures against commercial unmanned aerial vehicles weighing less than 20 kg or 55 pounds may comprise: 
     (a) a direction finding high fidelity RF receiver coupled with a receiving omnidirectional antenna and a receiving directional antenna for detecting an RF signature of a flying unmanned aerial vehicle, and a spectral signal identifier processor for analyzing the RF signature for identifying a set of spectral signatures of the unmanned aerial vehicle and eliminate electromagnetic clutter present in the typical UAS RF spectrum; 
     (b) a modified radar system originally intended for detection of terrestrial (Surface) targets, provided with a radar clutter and target filter processor for providing input to an azimuth and elevation vector coordinate data processor for determining the location of the unmanned aerial vehicle; and 
     (c) a signal generator that produces at least one tailored signal based on the spectral signatures of the unmanned aerial vehicle and a variable strength amplifier that generates an output power, an antenna alignment assembly for adjusting the alignment of a transmitting directional and focused antenna based on the location of the unmanned aerial vehicle as determined by the azimuth and elevation vector coordinate data processor, the signal generator and amplifier coupled with the transmitting antenna to send at least one signal to the unmanned aerial vehicle to alter at least one of the speed, direction and altitude of the unmanned aerial vehicle. 
     The system for providing integrated detection and countermeasures against unmanned aerial vehicles may further comprise: a Multiband LNA Assembly for amplifying received signals from the receiving omnidirectional and receiving directional antennae and transmitting signals to an Uplink Receive Host Workstation that sends information to the spectral signal identifier processor where the type of unmanned aerial vehicle is identified using a database of known spectral signal wave information for known unmanned aerial vehicles, and a Frequency and Wave Form Parameters unit coupled to a Modulation Look Up Table coupled to an ECM Modulation Type Select unit that is coupled to the signal generator that produces at least one tailored signal which is then transmitted in a highly focused and variable strength beam precisely aimed at the subject unmanned aerial system. 
     The system for providing integrated detection and countermeasures against unmanned aerial vehicles may further comprise a Receive Blanking unit that forces the receiving omnidirectional and a receiving directional antenna to stop receiving a radio frequency being transmitted by the transmitting directional and focused antennae. 
     The system for providing integrated detection and countermeasures against unmanned aerial vehicles may further provide an azimuth and elevation vector coordinate data processor that uses a spherical coordinate system for three-dimensional space wherein three numbers specify the position of a point measured in latitude, longitude and elevation obtained from the radar. 
     The system for providing integrated detection and countermeasures against unmanned aerial vehicles may further comprise a laser range finder and wherein the azimuth and elevation vector coordinate data processor uses a spherical coordinate system for three-dimensional space wherein three numbers specify the position of a point measured in latitude, longitude and elevation obtained from the laser range finder and associated computational algorithms. 
     The system for providing integrated detection and countermeasures against unmanned aerial vehicles may further comprise Electro-Optical and Infrared Sensors and associated computational algorithms and co-located with a Laser Range Finder to provide a comprehensive, multi-purpose targeting system that incorporates a fire-control capability and digital display to the system operator/HIL that shows the field of view of the suspect UAS target(s) along with vital pieces of data including range-to-target, target velocity, elevation, azimuth, wind velocity and direction, deterrent zone size, countermeasure type, temperature, barometric pressure and time of day. 
     The system for providing integrated detection and countermeasures against unmanned aerial vehicles may employ at least one tailored signal produced by the signal generator that is an electronic counter measure either specifically calculated or selected using modulation lookup table to determine a broad range of RF signatures used by the flying unmanned aerial vehicle utilizing a database library of specific radio frequencies characteristics common to unmanned aerial vehicles 
     The system for providing integrated detection and countermeasures against unmanned aerial vehicles may further employ at least one tailored signal produced by the signal generator is an electronic counter measure either specifically calculated or selected using modulation lookup table to determine a broad range of RF signatures used by the flying unmanned aerial vehicle utilizing a database library of specific radio frequencies characteristics common to unmanned aerial vehicles, is augmented by the observed frequencies detected by the RF detection. 
     The system for providing integrated detection and countermeasures against unmanned aerial vehicles may further employ at least one tailored signal produced by the signal generator that is an electronic counter measure either specifically calculated or selected using modulation lookup table to determine a broad range of RF signatures used by the flying unmanned aerial vehicle utilizing a database library of specific radio frequencies characteristics common to unmanned aerial vehicles this tailored signal may vary from the received signal in that a harmonic of the received signal may prove more effective in deterring the suspect UAV than the actual received signal. 
     The system for providing integrated detection and countermeasures against unmanned aerial vehicles may further employ at least one tailored signal produced by the signal generator that is an electronic counter measure either specifically calculated or selected using modulation lookup table to determine a broad range of RF signatures used by the flying unmanned aerial vehicle utilizing a database library of specific radio frequencies characteristics common to unmanned aerial vehicles, use of the frequency harmonic will allow reduced transmit power and minimize unintended collateral effects. 
     The system for providing integrated detection and countermeasures against unmanned aerial vehicles may further employ a transmitting directional and focused antenna that is a component of a directional transmitting antenna array. 
     The system for providing integrated detection and countermeasures against unmanned aerial vehicles may further employ a capability to engage an airborne UAS/UAV in either a destructive (kinetic) or a non-destructive (non-kinetic) manner. 
     The system for providing integrated detection and countermeasures against unmanned aerial vehicles may further comprise a means to accept non-system generated suspect sUAS identification and location information received from outside sources and to detect and track traditional commercial sUAS/UAV containing or not containing electronic transponder identification technology and a means to detect and track non-traditional aerial systems (Manned or unmanned) with similar spectral signatures operating in similar low altitude environments. 
     The system for providing integrated detection and countermeasures against unmanned aerial vehicles may further comprise a secure control network (using existing infrastructure or dedicated high bandwidth point-to-point communications hardware) that allows non-collocated emplacement of system elements  102  ( FIG.  2   ),  103  ( FIG.  3   ) and  104  &amp;  105  ( FIG.  4   ) to provide control of the system from remote locations or add additional sensors from remote sources. 
     More Detailed Non-Limiting Example Embodiments 
     Referring to  FIGS.  1 A- 4    there are shown schematic representations of the components of an integrated detection, tracking, identification/classification and countermeasure system  100  for use against small unmanned aerial systems (sUAS)  44 . In particular,  FIG.  1 A  shows an example non-limiting embodiment of an overall system  100 . 
     In  FIG.  1 A , a multiband high gain directional antenna array with vertical polarization transmits multiband high gain RF signals. Matrix Directional Transmit Antenna Array—designated as  10  in  FIGS.  1 A and  2   , is a signal processing technique used in sensor (Antenna) arrays for directional signal transmission; this is achieved by combining elements in a phased array in such a way that signals at particular angles experience constructive interference while others experience destructive interference; this equipment can be purchased “Off-The-Shelf” and one common manufacturer of this type of equipment is Motorola. Directional Antenna—designated as  10  in  FIGS.  1 A and  2 , and  12    in  FIGS.  1 A and  3   , may comprise in one non-limiting embodiment a class of directional or beam antenna that radiates greater power in one or more directions allowing for increased performance on transmits and receives and reduced interference from unwanted sources. These transmitted RF signals are specifically generated to interrupt or “spoof” the UAS/UAV on-board receivers or any other destructive/non-destructive deterrent. 
     A receive omnidirectional antenna array  12  is used to refine the inbound azimuth of the suspect sUAS  44  and can produce an X, Y coordinate when the RF signal is detected by more than one RF receiver being utilized with the system. Receive Directional Antenna Array—designated as  12  in  FIGS.  1 A and  3   , refers to multiple receiving antennae arranged such that the superposition of the electromagnetic waves is a predictable electromagnetic field and that the currents running through them are of different amplitudes and phases; this equipment can be purchased “Off-The-Shelf” and one common manufacturer of this type of equipment is Motorola and WiNRADIO. 
     A receive omnidirectional antenna array  14  provides 360° alerting and cueing data which allows the directional antenna  12  to be precisely aimed at the suspect sUAS  44 . Omni-directional Antenna—designated as  14  in  FIGS.  1 A and  3   , may comprise a class of antenna which receives or transmits radio wave power uniformly in all directions in one plane, with the radiated power decreasing with elevation angle above or below the plane, dropping to zero on the antenna&#39;s axis. Receive Omni Antenna Array—designated as  14  in  FIGS.  1 A and  3   , may comprise a class of antenna that receives radio wave power uniformly in all directions in one plane; this equipment can be purchased “Off-The-Shelf” and one common manufacturer of this type of equipment is Motorola. 
     EO/IR sensor  16  (electro-optical and/or infrared) may be collocated with LRF (laser range finder) with target acquisition and fire control system. Electro-Optical and Infrared Sensors—designated as  16  in  FIGS.  1 A and  4   , is a combination of a standard high definition video camera capable of viewing in daylight conditions and an infrared video camera capable of viewing in the infrared light perspective; both camera systems can be purchased “Off-The-Shelf” as common technology, one common manufacturer of this type of camera systems is FLIR Systems. IR—infrared is invisible (to the human eye) radiant energy, electromagnetic radiation with longer wavelengths than those of visible light, extending from the nominal red edge of the visible spectrum at 700 nanometers (frequency 430 THz) to 1 mm (300 GHz). Laser Range Finder—designated as  16  in  FIGS.  1 A and  4   , is a rangefinder which uses a laser beam, usually pulsed, to determine vital pieces of data including range-to-target, target velocity, deterrent angle, compass heading, wind velocity and direction, deterrent zone size, countermeasure type, temperature, barometric pressure and time of day. This equipment can be purchased “Off-The-Shelf” and one common manufacturer of this type of equipment is TrackingPoint. This LRF-sensor arrangement  16  provides images for recognition of a suspect sUAS  44 . LRF sensor arrangement  16  may also provide an X, Y, Z coordinate for the target  44  that is detected. 
     An automatic antenna alignment assembly  18  provides precision antenna alignment based on the X, Y, Z data produced by a radar system  43  and LRF system  16 , for both the interdiction and directional antennas. Automatic Antenna Alignment Assembly—designated as  18  in  FIGS.  1 A,  2  and  3   , and as  22  in  FIGS.  1 A and  4   , is specialized electronic equipment specifically designed to automatically point the directional antennae and or camera, laser systems to the desired location, namely a small unmanned aerial vehicles/systems (sUAS) designated as a target  44  in  FIG.  1 A , based on longitude and or latitude information gained or received by the receiving antennae, designated as  12  and  14  in  FIGS.  1 A and  3   , and or radar antennae designated as  43  in  FIGS.  1 A and  4   ; this specialized equipment can be purchased from and is proprietary to enrGies Engineering located in Huntsville, Ala. 
     A multiband LNA (low noise amplifier) assembly  20  amplifies the low power waveform received by antennas  12 ,  14  for use by other processing functions. Multiband Low Noise Amplifier (LNA) Assembly—designated as  20  in  FIGS.  1 A and  3   , is a multi-radio frequency electronic amplifier used to amplify possibly very weak signals, for example captured by an antenna. 
     An automatic antenna alignment assembly  22  similarly provides precision antenna alignment based on the X, Y, Z data produced by the radar system  43  for the LRF subsystem and the EO/IR sensor  16 . 
     High fidelity RF receivers are coupled to a host workstation CPU  24 . CPU  24  executes control signal processing algorithms based on software instructions stored in non-transitory memory. UplinkNideo Standard Definition (SD) Receiver &amp; Host Workstation—designated as  24  in  FIGS.  1 A and  3   , is a connection from the antennae to the video encoder where the information is processed by the main computer network; the uplink equipment can be purchased “Off-The-Shelf” and one common manufacturer of this type of equipment is Cisco Systems; the video receiver and main computer is also “Off-The-Shelf” technology and are readily available from numerous manufacturers. 
     An azimuth and elevation vector coordinate data processor  26  is used to calculate azimuth and elevation of target  44 . Azimuth and Elevation Vector Coordinate Data—designated as  26  in  FIGS.  1 A and  4   , is specialized algorithm software that has been developed to be used with a spherical coordinate system for three-dimensional space where three numbers specify the position of a point measured in latitude, longitude and elevation obtained from the LRF &amp; EO/IR Sensors designated as  16  in  FIGS.  1 A and  4    that includes a Laser Range Finder, and/or Radar designated as  43  in  FIGS.  1 A and  4   . 
     Uplink Video/Radio Transmitter Assembly—designated as  28  in  FIGS.  1 A and  2   , is a device that will take the received radio or video frequency information from database libraries designated as  36  in  FIGS.  1  and  3 ,  40    in  FIGS.  1 A- 3 , and  42    in  FIGS.  1 A and  3    and send it through a radio amplifier designated as  34  in  FIGS.  1 A — 3  to a transmitting directional antenna or matrix directional transmit antenna array designated as  10  in  FIGS.  1 A and  2   ; this equipment can be purchased “Off-The-Shelf” and one common manufacturer of this type of equipment is Motorola. 
     An Empower 1189-BVM3 wideband HPA assembly with a receive blanking unit  30  is provided. Blanking—designated as  30  in  FIGS.  1 A,  2  and  3    is the time between the last radio transmitting signal and the beginning of the next radio transmitting signal. Receive Blanking—designated as  30  in  FIG.  1 A- 3   , is specialized algorithm software that has been developed to stop the receiving antennae, designated as  12  and  14  in  FIGS.  1 A and  3   , from receiving radio frequency signals during the time that the counter measure transmitting frequency, designated as  34  in  FIGS.  1 A- 3   , is being transmitted by directional transmitting antennae, designated as  10  in  FIGS.  1 A and  2   , for the purpose of deterrence or interdiction of the suspect unmanned aerial vehicle/system, designated as a target  44  in  FIG.  1 A , identified as a known threat. 
     A sensor fusion processor  32  includes a direction detect and range estimator that estimates direction and range of target  44  based upon inputs received from the radar  43  and the LRF  16 . Direction Detection and Range Estimation—designated as  32  in  FIGS.  1 A- 4   , is specialized algorithm software that has been developed to detect a suspected target or signal of interest and calculated to obtain the azimuth and distance to that target or signal of interest based on data obtained by the Radio Frequency (RF) detection section  103  in  FIG.  3   , the Radar detection section  104  in  FIG.  4   , and the Electro Optical/Infrared (EO/IR,) ( 16 ) and co-located LRF (Laser Range Finder) ( 16 ) detection section  105  in  FIG.  4   . DF—designated as  12  in  FIGS.  1 A and  3   , Direction Finding refers to the measurement of the direction from which a received signal was transmitted; this can refer to radio or other forms of wireless communication. Sensor Fusion Processor—Designated as number  32  in  FIGS.  1 A,  2 ,  3 , and  4    is a control system processor which integrates the discrete data from all inputting sensors—This set of algorithms and processes provides the Human in the Loop (HiL) a visual display of subject location and type classification, as well as EO/IR imagery; overlaid on a moving map display; and includes the interdict command logic. These control functions are available via a service on our system secure internal network. 
     A Keysight N9310A RF signal generator with multiple modulation sources is coupled to an ECM modulation type selector  38 . Electronic Counter Measure (ECM) Modulation Type Select—designated as  38  in  FIGS.  1 A- 3    is specialized algorithm software that has been developed to help narrow down the radio frequency identified by a modulation lookup table of the specific unmanned aerial vehicle/system of interest, designated as a target  44  in  FIG.  1 A , utilizing a database library that was created and categorized with the specific radio frequencies common to all unmanned aerial vehicles/systems. A Spectral Signal Detect and Type Identifier  36  contains an RF library in databases of current, previously stored and new wave forms and frequencies of sUAS  44 . Spectral Signal—designated as  36  in  FIGS.  1 A and  3   , the frequency spectrum of a time-domain signal is a representation of that signal in the frequency domain. Spectral Signal Detection and Type Identification—designated as  36  in  FIGS.  1 A and  3   , is specialized algorithm software that has been developed to detect and identify unmanned aerial vehicles/systems utilizing a database library that was created and categorized with the spectral signatures common to all unmanned aerial vehicles/systems. 
     A frequency and waveform parameter generator  40  is used to specify frequency and waveform parameters for transmission. Frequency and Waveform Parameters—designated as  40  in  FIGS.  1 A- 3   , Is specialized algorithm software that has been developed to identify unmanned aerial vehicles/systems utilizing a database library that was created and categorized with the specific radio frequency waveform common to all unmanned aerial vehicles/systems. 
       FIG.  2    shows a countermeasure and deterrent section couple to the multiband high gain directional antenna array  10 . In this example, an automatic antenna alignment assembly  18  may be mechanically and/or electrically coupled to the antenna array  10  to set and change the azimuth and elevation of the antenna. As shown in  FIG.  2   , the automatic antenna alignment assembly  18  may include various components including a pan/tilt unit (PTU)  18   a , a magnetic compass  18   b , a position location modem  18   c , and a power and signal processor  18   d . The automatic antenna alignment assembly  18  is controlled by the sensor fusion processor/identification subsystem  32  including a detection and range estimation processor. The detection range estimation processor uses received sensor signals to identify potential targets  44 , and then controls the automatic antenna alignment assembly  18  to move and/or reconfigure the multiband high gain directional antenna array in order to beam transmission signals at the target. A multiband antenna array  10  receives signals to transmit from the Empower 1189-BVM3 wideband HPA assembly, which is coupled to a system power and system monitor  99 . The Empower unit  28  interacts with a Keysight N9310A RF signal generator with multiple modulation sources  34 , thereby generating particular signals with particular modulation superimposed thereon for transmission by antenna array  10 . 
     ECM modulation configuration data and receive blanking signal unit  30  interacts with the Keysight unit  34 . Modulation Function Generation—designated as  34  in  FIGS.  1 A- 3   , Is specialized algorithm software that has been developed to transmit (Jam) a specific radio frequency, designated by  38  in  FIGS.  1 A- 3  and  42    in  FIGS.  1 A and  3   , which is unique to a specific unmanned aerial vehicles/systems utilizing a database library that was created and categorized with the specific radio frequencies used on all common unmanned aerial vehicles/systems. The ECM modulation configuration data unit  38  in turn receives input signals from the identification subsystems  30 ,  40 . Modulation Lookup Table—designated as  42  in  FIGS.  1 A and  3   , is specialized algorithm software that has been developed to identify the broad range of radio frequencies being used by a specific unmanned aerial vehicle/system of interest, designated as a target  44  in  FIG.  1 A , utilizing a database library that was created and categorized with the specific radio frequencies common to all unmanned aerial vehicles/systems. Identification subsystem  30  uses receive blanking control, whereas the identification subsystem  40  uses frequency waveform algorithms. 
       FIG.  3    shows the example non-limiting radio frequency detection section  103 . In this example, the received directional antenna array  12  provides its received signal output to a WD-3300 direction finding system  20 . The RF receiving omnidirectional antenna  14  provides its received signals to an MS-811A wideband multichannel monitoring system  20 ′. These receivers provide modulated signals to the uplink/video SD receivers/host work station/CPU  24  that executes direction detect and range estimation algorithms under software instruction control stored in non-transitory memory (sometimes with humans in the loop). The CPU  24  operates in conjunction with ECM modulation type and data selection  38  and frequency and waveform parameter selection algorithm  40 . A spectral signal detected type identification modulation data algorithm  36  and receive blanking control  30  also operates in conjunction with CPU  24 . Receive blanking control  30  provides its receive blanking output to the interdictions subsystem  34 . The ECM modulation type and data selection  38  similarly provides its output to an interdiction subsystem  42  based upon ECM modulation and configuration data. The CPU  34  provides an output to an interdiction subsystem A4 system with steering data  18 , and receives inputs from the detection subsystem sensor azimuth and elevation data  46 . 
       FIG.  4    shows an example non-limiting radar detection section  104  and EO/IR/LRF detection section  105 . In this example, the radar detection section  104  includes, for example, an X-band radar such as a Vista Smart Sensor SSSR  43 . The power output of the X-band radar transceiver will be selected for desired range. The Vista smart sensor radar processor SSSR  33 ′ coupled to the radar detection section  43  may provide azimuth and elevation vector coordinate data to unit  26 . Target clutter and filter algorithms  45  may be used and/or executed by the Vista smart sensor radar processor SSSR  43 ′. The EO/IR/LRF detection section  16  may provide its output as explained above to an automatic antenna alignment assembly  22 . The automatic antenna alignment assembly  22  may be informed by the azimuth and elevation vector coordinate data  26 . The azimuth and elevation vector coordinate data  26  may operate in cooperation with a detect direction and range estimation process the sensor fusion processor  32  implements. STC—Slew To Cue, the autonomous actions of electronic, radio or optical sensors to rotate using an automatic antenna alignment assembly designated as  18  in  FIGS.  1 A- 3 , and  22    in  FIGS.  1 A and  4    to move and point cameras  16  in  FIGS.  1 A and  4    and countermeasures  10  in  FIGS.  1 A and  2    in the direction of a suspect target  44  in  FIG.  1 A , based on input from data processed by components  26  in  FIGS.  1 A and  4 , and  46    in  FIGS.  1 A,  3  and  4   , thus, keeping the “cued” targets in view at all times with or without human intervention. 
       FIG.  5    shows an example non-limiting flow chart that describes operation of the embodiment shown in  FIGS.  1 A- 4   . Upon initial RF detection of a target  44  (block  510 ), and/or initial radar detection block  510   a , the system may process these signals to identify a preliminary position (X, Y, Z) of the target (block  510   b ). The optical/IR/laser range finder may be used to derive a more precise X, Y, Z location, and imagery is fed to the sensor fusion processor (block  520 ). The system may then refine the X, Y, and Z coordinate position of the target and analyze received signatures and then begin tracking the target (block  520   a ). The system may next select a deterrent mode form and frequency for use in interdiction (block  520   a ). The system may then use sensor data fusion to yield a target ID/classification with or without a human in the loop (block  530 ). HiL—Designated as part of sensor fusion processor  32  in  FIGS.  1 A,  2 ,  3  and  4    is the system control position allowing the system operator or also referred to as the Human in the Loop (HiL) the ability to monitor all system functions/displays and has the opportunity to override the automated functions of the system. The computers and/or a human in the loop may observe the EO/IR imagery and make deter/non-deter decision (block  530 ). If the decision is to deter, then interdiction is initiated (block  540 ). Such interdiction may result from the application of a highly tailored narrow beam RF pulse which is generated, amplified and transmitted along the azimuth and elevation determined in the tracking processes with power based on the range to the target (block  540 ). 
       FIG.  5    thus represents a simplified visual over-view of the system processes that occur, from start to finish, in detecting ( 510 ), tracking ( 520 ), identification/classification ( 530 ) and deterring ( 540 ) a sUAS ( 44 ).
         1. A first function of the system is detecting a suspect sUAS target as reflected in sections  103 - 105  and  510  of  FIG.  3 - 5   .   2. The second function of the system is tracking a suspect sUAS target as reflected in sections  103 - 105  and  520  of  FIG.  3 - 5   .   3. The third function of the system is identifying a suspect sUAS target as reflected by sections  103 - 105  and  530  of  FIG.  3 - 5   .   4. The fourth function of the system is a deterrent targeting a suspect sUAS as reflected by section  102  and  540  of  FIG.  3 - 5   . This element of the system may be augmented with a destructive element consisting of a kinetic weapon system but is currently illustrated in  FIG.  1 A  using a non-kinetic RF deterrent.       

     In more detail, the first function of the system is to detect the Radar and RF signatures of a suspect sUAS flying near or within the system&#39;s detection boundaries. All sUAS&#39;s have a distinct set of spectral signatures (sound, heat, radar cross section, radio frequency wave pattern) detected by a spectral signal identifier processor  36 . This fact is the basis for the detection sections  103 - 105  of the system  100  of the non-limiting embodiments(s). Section  510  of  FIG.  5   , Section  104  of  FIG.  4    and Section  103  of  FIG.  3    of the example non-limiting technology herein are used for the detection process. This process begins with the radar  43  and/or the Receive Omni Antenna Array  14  detecting the presence of an airborne sUAS  44  within the defined area of protection. Any suspect sUAS  44  detected by the radar  43  produces radar-generated signature that is compared with known radar signatures, stored within the radar library database  43 , of common sUAS systems to verify that the suspect target is a sUAS. The system of the non-limiting embodiments(s) will use a proven high-end direction finding (DF) equipment  12 ,  14  and a high fidelity RF receiver  24  coupled with omnidirectional and directional antennae  12  and  14  to detect the communication link between a sUAS  44  and its operator. When the DF equipment  12 ,  14  has detected a communication link of a sUAS within the system boundaries, the receive host workstation  24  will analyze the radio frequency wave signature and confirm that the RF detected is from a sUAS. 
     This identification process also applies when a radar unit  43  is integrated with the DF equipment. This element of the system may be augmented with additional signature detection elements consisting of acoustic sensors but is currently illustrated in  FIG.  1 A  using the primary radar sensors  43 , RF sensors  12 ,  14  and electro optical sensor  16 . In addition, the RF receiver  20  scans for the presence of known C2 uplink or downlink and video uplink or downlink frequencies commonly used by sUAS and compare the received signature against known RF signatures stored within a library database  36 . Successful matches generate a target file and release the X, Y, and Z coordinate data  26  and  46  of that target to the A4 units  18  &amp;  22  to begin the process of tracking. Integrating multiple Direction Finding (DF) equipment  12 ,  14  to the system of the non-limiting embodiments(s) will increase the precision in obtaining the azimuth that the sUAS is flying. Integrating radar equipment  43  provided with a radar clutter and target filter processor  45 , with the direction finding (DF) equipment and LRF  16  will provide the non-limiting embodiments(s) the ability to determine with greater accuracy the altitude and azimuth of the sUAS  44  at the time of discovery and during the time it remains within the systems detection boundaries. 
     The coordinate data obtained from DF  26 ,  46 , radar unit  43  and LRF  16 , is then sent to the direction detect and range estimation, (Sensor Fusion Processor)  32 , where algorithms will be used to send sUAS location coordinates to the Automatic Antenna Alignment Assembly (A4)  22 ,  18 . Put another way, using an enhanced analytic function commonly referred to as “Slew-To-Cue”, the non-limiting embodiments(s) causes autonomously, the actions of the electronic, radio frequency sensors and/or optical sensors to rotate using the automatic antenna alignment assembly  18 ,  22  to move and point cameras and collocated LRF  16  with countermeasures antenna  10 , in the direction of a suspect sUAS  44  based on input from data processed by the azimuth and elevation unit  26 ,  46 , thus, keeping the “cued” targets in view at all times with or without human intervention. This information will then direct the Automatic Antenna Alignment Assembly (A4)  22  to point the Electro-Optical and Laser Range Finding unit  16  at the sUAS. This precise aiming function enables highly accurate visual and non-visual imagery to be captured of the suspect sUAS,  44 . By comparison of the captured imagery against known and continuously improving profile databases maintained or accessed by sensor fusion processor  32 , sophisticated pixel and histogram comparison algorithms will confirm or deny that the target being viewed is a sUAS and a threat assessment is then generated. 
     The detect elements operate with unique software translating discernable signatures (Radar, RF, EO/IR) into identifiable data aiding in the detection and identification/classification process. All signature data (Radar, RF &amp; EO/IR) is then processed and coupled with the LRF  16  data to generate a reference azimuth and elevation  26 ,  46  of the suspect sUAS  44 . The information generated by the systems detection section is then passed electronically to the direction and range estimation processor, (Sensor Fusion Processor)  32 , to yield a sUAS location and overlaid on the system mapping display to be viewed by the system operator/HiL. The RF detection receiver and processors  24  determine the: radio (carrier) frequency, pulse width or pulse duration, pulse repetition interval, signal amplitude and polarization; to a lesser extent the scan pattern and rate. These characteristics are then compared within the library database  36  to the known characteristics of the most likely sUAS RF element profiles. This analytic function is performed in an automated process resident in system detect element  103 . 
     The example non-limiting technology herein is intended to utilize all of the multi-sensors described above to obtain X, Y and Z (Longitude, Latitude and Altitude) of the suspect sUAS. Each sensor may be used independently or collectively. The Radar in  FIG.  2    can be use in stand-alone mode to provide the X, Y, Z coordinates to Azimuth and Elevation Vector Coordinate Data Processor  46  and Directional Detect and Range Estimation function of sensor fusion processor  32  that enables the slew to clue (STC) to the EO/IR/LRF  16  and Receive Directional Antenna  12  and or Deterrent system Antennae  10 . The RF receive antenna  12  and Omni-directional antenna  14  in  FIG.  3    can also provide the X and Y coordinates in stand-alone mode to activate the Automatic Antenna Alignment Assembly  18  &amp;  22 , the Multiband High gain Directional Antenna Array  10  and EO/IR/Laser Range Finder  16  as displayed in  FIGS.  1 A and  2   . This automated function points the directional antennae  10  and or EO/IR and Laser Range Finder  16  to the desired location based on longitude and or latitude information gained or received by the receiving antennae, designated as  12  and  14  in  FIGS.  1 A and  3   , and or radar antennae designated as  43  in  FIGS.  1 A and  4   . Additionally, non-system generated suspect sUAS identification and location information received from outside sources may be used in the calculation processes within the system of example non-limiting technology herein. 
     The example non-limiting technology herein begins calculation of the optimized waveform and necessary power and frequency to interfere with the suspect sUAS on-board electronic controls and communication links. Simultaneously, the threat assessment and sUAS identity information is made available via visual display to the system operator/HiL providing an opportunity to override the interdiction sequence of the non-limiting embodiments(s) if desired. 
     A second function of the system,  520  of  FIG.  5   , is to track a suspect sUAS that is within the system boundaries or approaching a protected area. When a suspect sUAS nears or enters the system boundaries, azimuthal data obtained by the detection sections  103 ,  104  and  105  is sent to the automatic antenna alignment assembly  22  and  18 . Section  104  &amp; 105  of  FIG.  4    and Items  12 ,  14 ,  16 ,  20  &amp;  32  of  FIG.  3    of the non-limiting embodiments(s) are used for the tracking process. Coordinate data obtained by the radar  43 , Omni and Directional antennas  12 ,  14  and the LRF  16  are sent to the Sensor Fusion Processor  32  where a set of algorithms and processes provides the System Operator/HiL a visual display of continuous suspect sUAS  44  location as well as the EO/IR imagery and threat assessment, overlaid on a moving map display and includes the interdict command logic needed in Step  4 . The radar  43  will provides X, Y, Z location data and preliminary suspect sUAS identification based on the observed radar signature (cross-section, Doppler effect, polarization). The observed sUAS characteristics are compared in a signature library or database  43  of known sUAS of concern. This database is updated with observed characteristics and becomes more refined with use. These computational functions take place within  43  and are continuously refined as the suspect sUAS  44  is tracked. The system&#39;s control software/hardware provides this information to the integrated Electro-Optical (EO) and Infrared (IR) sensor  16 , which autonomously centers the field of regard of the EO/IR sensor to the known location of the suspect sUAS  44 . 
     The LRF  16 , assisted by the system of software/hardware, will then determine the precise X, Y, Z coordinates (X=longitude, Y=latitude, Z=altitude) of the suspect sUAS. The azimuth, elevation and distance is obtained by the Laser Range Finder  16 , and is transferred to the Azimuth and Elevation Vector Coordinate Data processor unit  26  that calculates the precise azimuth and elevation information and uses that to generate servo commands which drive the A4 system  18  controlling the Matrix Directional Transmit Antenna Array  10  via the Direction Detect and Range Estimation function of sensor fusion processor  32 ; to aim the associated equipment at the suspect sUAS  44 . This precise location and range information is provided to the countermeasure and deterrent section  102  of the system  100 . Using this data, the countermeasure and deterrent section  102  computes the RF spectral characteristics that will nullify control signals that the suspect sUAS expects to receive. A signal generator  34  produces a tailored signal and a variable strength amplifier  28  generates the output power required to cause the desired effect at the desired range to the targeted sUAS  44  as indicated within the fourth function of the system. 
     A third function of the system,  530  of  FIG.  5   , is to identify the sUAS that is approaching or within the system boundaries or protected area. Item  36  of  FIG.  3   , Item  43  of  FIG.  4    and Item  32  of  FIGS.  1 A,  2 ,  3  and  4    of the non-limiting embodiments(s) is the identification process. This process utilizes radar data obtained by Radar  43 , the RF data  36  gathered by the Receive Omni &amp; Directional Antenna Array  14  &amp;  12  combined with the visual and or heat signatures generated from the EO/IR camera system  16  to determine the type of sUAS and any payload the sUAS may have attached to it. This data is sent to the Sensor Fusion Processor  32  that integrates the discrete data from all inputting sensors listed above to aid in target identification and threat assessment. Further, a set of algorithms and processes continues to provide the System Operator/HiL a visual display of geo-referenced suspect sUAS  44  locations and type classification, as well as EO/IR imagery overlaid on a moving map display. These functions are described in a linear manner but are continuously updated, thereby increasing the positional and sUAS identification/threat assessment accuracy. 
     As this data is collected and refined, the interdiction RF waveform amplitude, pulse width and repetition frequency is also refined. The interdiction RF frequency is determined and will be a harmonic of the detected RF frequency controlling the suspect sUAS, thereby, increasing its effects on the sUAS control sensors and minimizing potential for unintended collateral effect. The system uses the hardware and software of the Radio Frequency (RF) detection section  103  and the associated known and observed communication radio frequencies signatures exhibited between the sUAS and its controlling operator, to include video data exchange, and compares it against the stored data (RF Database  42 ) of known sUAS control/video frequencies. The system also analyzes and determines the RF spectral characteristics needed to nullify the communication control signals of the suspect sUAS  44 . 
     During the identification process, the system will also conduct an automated threat assessment to determine if the suspect sUAS is carrying a payload of concern (size and shape) by comparing video/photo analytics and radar signatures, to include visual inspection/verification by the system operator, and evaluate other concerning data, such as detection of an encrypted video downlink, flight profile or course, to generate a continuous threat assessment. By comparing known non-threatening sUAS analytic profiles with known threatening sUAS profiles, the system data mining processes can classify a targeted sUAS with an initial threat level or advance to a higher threat level if additional concerning data is received or observed. The system continuously monitors the location and threat assessment information of the targeted sUAS allowing the system operator live information prior to deterring the sUAS with a non-kinetic interdiction response or destroy the sUAS if the system is armed with a kinetic countermeasure device. 
     The fourth function of the system,  540  of  FIG.  5   , is to deter/interdict the operation of a targeted sUAS that has entered into the system boundaries or protected area. Section  102  of  FIG.  2    and Item  32  of  FIGS.  1 A,  2 ,  3  and  4    of the non-limiting embodiments(s) is the deterrence process. This process can use either a non-destructive method to force the sUAS to land or return to its departure location or a destructive method in stopping/destroying a sUAS threat.  FIG.  5   , section  540 , represents a non-destructive method utilizing a Multi Band High Gain Directional antenna array  10  using vertical polarization to transmit RF signals directly at the targeted sUAS  44 . These RF waveforms are then used to disrupt the expected inputs to the onboard controller of the targeted sUAS  44 . However, depending on the operational environment; a non-destructive system may be augmented or coupled with a destructive system consisting of a kinetic weapon system. 
     The system&#39;s non-destructive deterrence against a targeted sUAS is achieved by transmitting the most advantageous RF frequency derived based on the identification information obtained from RF frequency database  42  and RF spectral analysis  36  derived in Step  2  and  3 . This concentrated Radio Frequency (RF) emission tuned to the specific sUAS characteristics identified by the spectral analysis during the detection process is obtained when the communications link, or any other RF emission generated by subject sUAS is detected by the Radio Frequency (RF) detection section  103  of the system. Information is passed through the Multiband LNA Assembly  20  and through the Uplink Receive Host Workstation  24 . The information is then sent to the Spectral Signal Detect and Type Identification unit  36  where the type of sUAS is determined based on a known sUAS RF profile database containing Spectral Signal Wave information  36 . When the Spectral Signal Waveform information is known the information is sent to the Frequency and Wave Form Parameters unit  40  where the analyzed RF data is sent to the Modulation Look Up Table  42 . When the Modulation characterization is made, that data is transferred to the ECM Modulation Type Select processor  38  where the non-limiting embodiments(s) creates a uniquely tailored waveform. The selected modulation waveform is then sent to the Uplink Video Transmitter Assembly  28 . That unit works in conjunction with the Receive Blanking unit  30 . When the Uplink Video Transmitter  28  is transmitting a radio signal the Receive Blanking unit  30  will force the DF antennae  12 ,  14  to stop receiving the radio frequency being transmitted by the Matrix Directional Transmit Antenna Array  10 . The radio frequency selected to disrupt the communication link between the targeted sUAS  44  and its&#39; operator is then transmitted by the Transmitter Assembly  28  using the Matrix Directional Transmit Antenna Array  10  aimed at the sUAS  44  via the Automatic Antenna Alignment Assembly  18 . The countermeasure and deterrent section  102  broadcasts this unique generated RF waveform using highly directional and focused antennae  10 . The system uses Blanking  30  at the time between the last radio transmitting signal and the beginning of the next radio-transmitting signal of the transmitted signal in accordance with the frequency and waveform parameters  40  to avoid negative internal effects to system  103 . 
     The countermeasure and deterrent section  102  of the system  100  interdicts the operation of a targeted sUAS in a non-destructive manner by using the non-destructive technology described above to generate an interdict transmission signal that is significantly higher gain (Stronger Signal) than the control signals produced from an operator control unit transmitting to the targeted sUAS  44 . The video downlink frequency is the initial target of the interdiction process. If this interruption is not sufficient to deter the targeted sUAS  44 , the RF transmitter will be tuned to the appropriate control frequency to disrupt the targeted sUAS  44  on-board electronics increasing the probability of the targeted sUAS  44  entering into its “Fail Safe Mode”. This action is sUAS specific and is based on the manufacturer design and sUAS operational capabilities. The interdict transmission will target both the sensor and the control electronics of the sUAS. The effects of the higher gain radio transmission will cause amongst other effects, servo-chatter and disruption of most on-board electronic processes resulting in the loss of control of the targeted sUAS  44  or forcing it to land or return back to its departure location (Fail Safe Mode). 
     The non-limiting embodiments(s) considers the differences based on the manufacturer design and operational capabilities of the sUAS on a case-by-case basis and tailors the systems countermeasure/deterrent response accordingly. The interdiction process may be augmented with electro-magnetic pulse technology, pulsed laser and is specifically designed to accept other current or future counter-measures used to defeat the sUAS&#39; electronics, motors and or navigation systems. In addition, a separate, system operated, sUAS can be dispatched with autonomous navigation data being supplied by the system of non-limiting embodiments(s) to locate and intentionally disable the opposing sUAS by flying into it, dropping a net on the threat, covering it with spray foam or liquid or capturing the opposing sUAS. 
     Example Non-Limiting Threat Assessment Process 
       FIG.  6    shows an example non-limiting sensor fusion and threat assessment process performed by sensor fusion processor  32 . In the example non-limiting embodiment, sensor fusion processor  32  receives and processes the inputs of many different sensors, i.e., radar  43 , radio frequency receiving antennas  12  and  14  (including the azimuth/elevation coordinates of receive directional antenna array  12 , optical/infrared sensor and laser range finder  16  (including associated azimuth and elevation information). Processing is performed based on video-photo analytics  32 B, direction, detection and range estimation  32 C, and a fusion process  32 D. 
     From the radar  43 , sensor fusion processor  32  receives information indicative of detected target presence, detected target size, detected target range, number of detected targets and three-dimensional (XYZ) position of each detected target. Radar  43  also provides information concerning detected target speed and direction. In some embodiments, the radar  43  provides such information in the form of a display image that sensor fusion processor  32  analyzes to extract useful information. In other embodiments, radar  43  may provide data packets encoding such information periodically, on demand or otherwise. 
     From directional RF antenna  12 , sensor fusion processor  32  receives information indicative of azimuth and elevation (direction in 2 dimensions) of a transmitting entity, signal strength of received transmissions, frequencies on which the transmissions are occurring (such information can be derived using a spectrum analyzer for example) and in some cases the content of transmission including identifiers and the like. 
     From omnidirectional RF antenna  12 , sensor fusion processor  32  receives signal strength of received transmissions, frequencies on which the transmissions are occurring (such information can be derived using a spectrum analyzer for example) and in some cases the content of transmission including identifiers and the like. The omnidirectional antenna  14  functions even when the directional antenna  14  is not (yet) aimed at the target. 
     From EO/IR/LRF  16 , sensor fusion processor  32  receives target range information, target direction information (three-dimensional position XYZ coordinates in the best case) as well as target movement and speed of movement information. In some embodiments, the sensor fusion processor  32  also receives images (IR, visible light or both) of the target that can help with target identification. 
     As can be seen in  FIG.  6   , the sensor fusion processor  32  uses different combinations of these sensor inputs to determine different characteristics concerning the target. For example, sensor fusion processor  32  can detect target location based on the RF related information, the radar information, the imagery information and the laser range finder information. The sensor fusion processor  32  may attempt to classify the target based on RF information, radar information and imagery. The sensor fusion processor  32  may determine a bearing/heading for the target and the speed of the target along that bearing/heading based on the radar and LRF information. The sensor fusion processor  32  may determine the size/shape of the target and presence of a payload on the target based on radar and imagery. The sensor fusion processor  32  may determine a flight profile for the target based on radar, imagery and LRF. 
     The sensor fusion processor  32  in the example non-limiting embodiment is able to process different inputs with different algorithm and then correlate or filter results to obtain a more accurate value than would be possible using single sensor inputs. For example, radar  43  and laser range finder  16  each provide target range information, but different conditions and factors such as weather, nature of the target, ambient lighting, interference and other factors can affect these two independent sensing mechanisms differently. The LRF  16  for example may be more accurate at closer ranges in lower light conditions, whereas the radar  43  may be more accurate at further ranges when there is no precipitation. Sensor fusion processor  32  takes such differences in sensor performance into account when weighting and filtering the different inputs in order to optimize accuracy and reliability. 
     Based on this multi-sensor analysis and data mining process via all available data inputs, the sensor fusion processor  32  creates a threat value (ThV) for each criterion and in particular uses a ranking methodology applied to the established logic of multi-criteria analysis to create a threat value (ThV) for each criteria which include; Location, Target Classification, Bearing, Speed, Payload, Size, and Flight Profile. The threat assessment (ThA) of a function (fx) of these values. The ThA is compared to a variable set of rules and results in a system generated interdict/monitor command. The ThA is outputted to an interdiction system ( 102 ) and displayed for a human in the loop (HIL). Part of the function of sensor fusion processor  32  is to develop a confidence factor that is used to determine whether to interdict and what type of interdiction to command. For example, potentially destructive interdiction is not commanded unless the confidence value is high. 
     Threat Assessment (ThA) in one non-limiting embodiment is the level of threat assigned a specific target after application of the analytic processes as well as potential data from external sources, data mining, as well as consideration of the ThV. ThA is based on the sum of ThV of each criteria which is derived from data provided by the systems input sensors: radar, RF detection, EO/IR imagery, and range. Each sensor that is currently functioning contributes to the algorithm based on that sensor&#39;s observed phenomenology. Fault tolerance is provided by continuing to operate with all available information even when one or more sensors is damaged, has failed or is otherwise not providing useful information. 
     Rule sets, which may be varied, specify the required interdiction action taken for a given ThA, e.g., ThA of  10  results in an immediate full power interdiction transmission, continuing until the target is neutralized; ThA of  1  generates a monitor only response. 
     As example: 
     
       
         
           
               
               
               
               
               
             
               
                   
               
               
                 Contributing Sensor 
                   
                   
                   
                 ThV 
               
               
                 Criteria 
                 Criteria 
                 ThV 
                 Weight 
                 (weighted) 
               
               
                   
               
             
            
               
                   
               
            
           
           
               
               
               
               
               
            
               
                 RF, Radar, Imagery, LRF 
                 Location 
                 3 
                 1 
                 3 
               
               
                 RF, Radar, Imagery 
                 Classification 
                 5 
                 1 
                 5 
               
               
                 Radar, LRF 
                 Bearing 
                 −1 
                 2 
                 −2 
               
               
                 Radar, LRF 
                 Speed 
                 1 
                 2 
                 2 
               
               
                 Radar, Imagery 
                 Payload 
                 5 
                 2 
                 10 
               
               
                 Radar, Imagery 
                 Size 
                 3 
                 1 
                 3 
               
               
                 Radar, Imagery, LRF 
                 Flight Profile 
                 3 
                 1 
                 3 
               
               
                 Threat Assessment (ThA) 
                   
                   
                   
                 24 
               
               
                   
               
            
           
         
       
     
     In this example, the ThA of  24  would result in immediate interdiction; the presence of an observable threatening payload. Such a ThA makes it a very high priority target. This assessment is an iterative process until the target either leaves the area of concern or is interdicted. 
     Glossary 
     Algorithm—a process or set of rules to be followed in calculations or other problem-solving operations by a computer 
     C2 Communications—Command and Control Communications links 
     Commercial—relating to or engaged in commerce (i.e., NON-military) 
     Counter—to offer in response or act in opposition 
     CUASs2—Counter Unmanned Aerial Systems of Systems, the system of the non-limiting embodiments(s) used to detect, identify/classify, track and deter or interdict small unmanned aerial vehicles or systems 
     Emitter—to send or give out a matter of energy 
     EO—Electro-Optics is a branch of electrical engineering and materials science involving components, devices and systems that operate by modification of the optical properties of a material by an electric field, thus it concerns the interaction between the electromagnetic (optical) and the electrical (electronic) states of materials 
     Fire control—The computer connection between the tracking optic and the fire control trigger, located at the system operator (HIL) console. The computer contains dozens of microprocessors and electronic, electro-optic, and electro-mechanical components that guide the release (firing) of the chosen countermeasure to ensure an accurate engagement over great distances 
     Frequency—the rate at which a vibration occurs that constitutes a wave, either in a material (as in sound waves), or in an electromagnetic field (as in radio waves and light), usually measured per second 
     Jam or Jammed or Jammers or Jamming—to interfere with or prevent the clear reception of broadcast signals by electronic means to become unworkable or to make unintelligible by sending out interfering signals by any means 
     Laser—a device that emits light through a process of optical amplification based on the stimulated emission of electromagnetic radiation 
     Matrix—an environment in which something develops 
     Mobile Platform (MP)—the system installed on any vehicle with the intent to move from one location to another location as needed to fulfill a short-term need in the detection, tracking, identification/classification and deterrence or interdiction of a small unmanned aerial system (sUAS) 
     Modulation—the process of varying one or more properties of a periodic waveform, called the carrier signal, with a modulating signal that typically contains information to be transmitted 
     Multi-Band—a communication device that supports multiple radio frequency bands 
     OTS—Off The Shelf refers to materials or equipment that currently exists and is readily available for purchased or use 
     Permanent Platform (PP)—the system installed at a specific location to fulfill a long-term need in the detection, tracking, identification/classification and deterrence or interdiction of a small unmanned aerial system (sUAS) 
     Pulse—a single vibration or short burst of sound, electric current, light, or other wave 
     RPA—Remotely Piloted Aircraft, aka UAV, UAS 
     RF—Radio Frequency is a rate of oscillation in the range of around 3 kHz to 300 GHz, which corresponds to the frequency of radio waves, and the alternating currents that carry radio signals 
     Target—something or someone of interest to be affected by an action or development 
     Threat—a declaration or an act of an intention or determination to inflict the destruction of property or harm, punishment, injury or death of person(s) 
     UAS—Unmanned Aerial System, (aka UAV, RPA) 
     UAV—Unmanned Aerial Vehicle, (aka UAS, RPA) 
     Uplink—the part of a network connection used to send, or upload, data from one device to a remote device 
     Vector—a quantity having direction as well as magnitude, especially as determining the position of one point in space relative to another 
     Watt—the system unit of power, equivalent to one joule per second, corresponding to the power in an electric circuit in which the potential difference is one volt and the current one ampere. 
     Waveform—a graphic representation of the shape of a wave that indicates its characteristics as frequency and amplitude. 
     While the invention has been described in connection with what is presently considered to be the most practical and preferred embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.