# US 11,307,291 B1 · Method and apparatus for estimating a path of an aerial vehicle > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,307,291 B1 - Document ID: US11307291B1 - Status: Granted - Kind: B1 - Application number: 17/352,906 - Filed: 2021-06-21 - Granted: 2022-04-19 - Earliest claimed: 2021-06-21 - Assignees: King Abdulaziz University - Applicants: King Abdulaziz University - Inventors: Abdulah Aljohani; Ubaid M. Al-Saggaf; Muhammad Moinuddin; Waleed Aldosari - Web page: https://patentgrep.com/patent/US11307291B1 ## CPC - G01S 7/38: Jamming means, e.g. producing false echoes - G01S 13/723: {by using numerical data} - B64U 10/13: Flying platforms - G01S 5/0294: {Trajectory determination or predictive filtering, e.g. target tracking or Kalman filtering} - G01S 11/06: using intensity measurements - G01S 13/04: Systems determining presence of a target (based on relative movement of target G01S13/56) - B64U 2101/17: for detecting, disrupting or countering communications - G01S 2205/03: Airborne - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - B64U: UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR ## Abstract Methods and apparatuses are provided for estimating a path of an aerial vehicle engaged in attacking network devices in a wireless communication network. A distance function corresponding to the aerial vehicle and a boundary node is determined based on an initial coordinate location of the aerial vehicle and an initial coordinate location of the boundary node. A function of jamming power received at the boundary node from the aerial vehicle is determined based at least on the first distance function and a transmission power of the boundary node. The function of jamming power represents a power associated with a jamming signal received from the aerial vehicle at the boundary node. A trajectory of the aerial vehicle at a plurality of time periods is estimated by the boundary node with an extended Kalman filter. The extended Kalman filter is determined based on the function of jamming power. ## Claims ### Claim 1 A method for estimating a path of an aerial vehicle engaged in attacking network devices over a wideband channel in a wireless communication network, the method comprising: receiving a plurality of jamming signals from the aerial vehicle at a plurality of base stations, wherein each base station has at least one of a transceiver and an antenna; determining, with circuitry of a processor, a first distance function corresponding to the aerial vehicle and a boundary node based on an initial coordinate location of the aerial vehicle and an initial coordinate location of the boundary node; determining, with circuitry of the processor, a function of jamming power received at the boundary node from the aerial vehicle based at least on the first distance function and a transmission power of the boundary node, wherein the function of jamming power represents a power associated with a jamming signal received from the aerial vehicle at the boundary node; and estimating, with circuitry of the processor, a trajectory of the aerial vehicle at a plurality of time periods by the boundary node based on an extended Kalman filter, wherein the extended Kalman filter is determined based on the function of jamming power. ### Claim 2 (depends on 1) The method of claim 1, wherein the estimating of the trajectory of the aerial vehicle at the plurality of time periods is performed by the boundary node locally, without collaborating with any other node in the network. ### Claim 3 (depends on 1) The method of claim 1, wherein the initial coordinate location of the aerial vehicle is represented by (xB, yB, zB) and the initial coordinate location of the boundary node is represented by (xJ, yJ, zJ) and the first distance function is represented by dJB, and dJB=√{square root over ((xB−xJ)2+(yB−yJ)2+(zB−zJ)2)}. ### Claim 4 (depends on 3) The method of claim 3, wherein the function of jamming power is represented by PJB, and PJB=Pt+k−10nlog10dJB+Xσ, wherein Pt represents the transmission power of the boundary node, k represents a constant depending on antenna characteristics of the boundary node, and Xσ represents a Gaussian noise with zero mean. ### Claim 5 (depends on 4) The method of claim 4, further comprising: determining a power received at an unaffected node from the boundary node; determining a distance ratio coefficient based at least on the power received at the unaffected node from the boundary node, the function of jamming power and a threshold value of a signal to noise ratio at an edge node, wherein the edge node is located at a threshold distance from the initial coordinate location of the aerial vehicle and the threshold distance is a maximum distance that the jamming signal can potentially jam any node in the network. ### Claim 6 (depends on 5) The method of claim 5, further comprising: determining a second distance function corresponding to the edge node and the boundary node based at least on the second distance function and the distance ratio coefficient; determining another function of jamming power received at the edge node from the aerial vehicle based at least on the function of jamming power and the distance ratio coefficient, wherein the another function of jamming power represents another power associated with another jamming signal received from the aerial vehicle at the edge node; determining a function of power received at the boundary node from the edge node based at least on the function of jamming power and the distance ratio coefficient, wherein the another function of jamming power represents a power associated with a signal received from the edge node at the boundary node; estimating the trajectory of the aerial vehicle at the plurality of time periods by the boundary node based on another extended Kalman filter, wherein the another extended Kalman filter is determined based on the function of jamming power, the another function of jamming power received at the edge node from the aerial vehicle, and the function of power received at the boundary node from the edge node. ### Claim 7 (depends on 6) The method of claim 6, wherein the distance ratio coefficient is represented by β, and β = 1 ⁢ 0 ( γ - P NB + P JB 1 ⁢ 0 ⁢ n ) , wherein PNB represents the power received at the unaffected node from the boundary node. ### Claim 8 (depends on 7) The method of claim 7, wherein the second distance function corresponding to the edge node and the boundary node is represented by dEB, and dEB=dJB (1−β)√{square root over ((xB−xJ)2+(yB−yJ)2+(zB−zJ)2)}(1−β). ### Claim 9 (depends on 8) The method of claim 8, wherein the another function of jamming power received at the edge node from the aerial vehicle is represented by PJE, and PJE=PJB−10nlog10(β). ### Claim 10 (depends on 9) The method of claim 9, wherein the function of power received at the boundary node from the edge node is represented by PEB, and PEB=PJB−10nlog10(1−β). ### Claim 11 A system for estimating a path of an aerial vehicle engaged in attacking network devices over a wideband channel in a wireless communication network, a plurality of base stations, wherein each base station has at least one of a transceiver and an antenna, and a processor with circuitry, wherein the plurality of base stations is configured to receive a plurality of jamming signals from the aerial vehicle and; wherein the circuitry is configured to: determine a first distance function corresponding to the aerial vehicle and a boundary node based on an initial coordinate location of the aerial vehicle and an initial coordinate location of the boundary node; determine a function of jamming power received at the boundary node from the aerial vehicle based at least on the first distance function and a transmission power of the boundary node, wherein the function of jamming power represents a power associated with a jamming signal received from the aerial vehicle at the boundary node; and estimate a trajectory of the aerial vehicle at a plurality of time periods by the boundary node based on an extended Kalman filter, wherein the extended Kalman filter is determined based on the function of jamming power. ### Claim 12 (depends on 11) The apparatus of claim 11, wherein the estimating of the trajectory of the aerial vehicle at the plurality of time periods is performed by the boundary node locally, without collaborating with any other node in the network. ### Claim 13 (depends on 11) The apparatus of claim 11, wherein the initial coordinate location of the aerial vehicle is represented by (xB, yB, zB) and the initial coordinate location of the boundary node is represented by (xJ, yJ, zJ) and the first distance function is represented by dJB, and dJB=√{square root over ((xB−xJ)2+(yB−yJ)2+(zB−zJ)2)}. ### Claim 14 (depends on 13) The apparatus of claim 13, wherein the function of jamming power is represented by PJB, and PJB=Pt+k−10nlog10dJB+Xσ wherein Pt represents the transmission power of the boundary node, k represents a constant depending on antenna characteristics of the boundary node, and Xσ represents a Gaussian noise with zero mean. ### Claim 15 (depends on 14) The apparatus of claim 14, further configured to: determining a power received at an unaffected node from the boundary node; determining a distance ratio coefficient based at least on the power received at the unaffected node from the boundary node, the function of jamming power and a threshold value of a signal to noise ratio at an edge node, wherein the edge node is located at a threshold distance from the initial coordinate location of the aerial vehicle and the threshold distance is a maximum distance that the jamming signal can potentially jam any node in the network. ### Claim 16 (depends on 15) The apparatus of claim 15, further configured to: determining a second distance function corresponding to the edge node and the boundary node based at least on the second distance function and the distance ratio coefficient; determining another function of jamming power received at the edge node from the aerial vehicle based at least on the function of jamming power and the distance ratio coefficient, wherein the another function of jamming power represents another power associated with another jamming signal received from the aerial vehicle at the edge node; determining a function of power received at the boundary node from the edge node based at least on the function of jamming power and the distance ratio coefficient, wherein the another function of jamming power represents a power associated with a signal received from the edge node at the boundary node; estimating the trajectory of the aerial vehicle at the plurality of time periods by the boundary node based on another extended Kalman filter, wherein the another extended Kalman filter is determined based on the function of jamming power, the another function of jamming power received at the edge node from the aerial vehicle, and the function of power received at the boundary node from the edge node. ### Claim 17 (depends on 16) The apparatus of claim 16, wherein the distance ratio coefficient is represented by β, and β = 1 ⁢ 0 ( γ - P NB + P JB 1 ⁢ 0 ⁢ n ) , wherein PNB represents the power received at the unaffected node from the boundary node. ### Claim 18 (depends on 17) The apparatus of claim 17, wherein the second distance function corresponding to the edge node and the boundary node is represented by dEB, and dEB=dJB (1−β)√{square root over ((xB−xJ)2+(yB−yJ)2+(zB−zJ)2)}(1−β). ### Claim 19 (depends on 18) The apparatus of claim 18, wherein the another function of jamming power received at the edge node from the aerial vehicle is represented by PJE, and PJE PJB−10nlog10(β). ### Claim 20 (depends on 19) The apparatus of claim 19, wherein the function of power received at the boundary node from the edge node is represented by PEB, and PEB=PJB−10nlog10(1−β).