trilateration

问题 I am trying to create an android smartphone application which uses Apples iBeacon technology to determine the current indoor location of itself. I already managed to get all available beacons and calculate the distance to them via the rssi signal. Currently I face the problem, that I am not able to find any library or implementation of an algorithm, which calculates the estimated location in 2D by using 3 (or more) distances of fixed points with the condition, that these distances are not

来源： https://stackoverflow.com/questions/58228533/issues-implementing-the-fang-algorithm-for-tdoa-trilateration

来源： https://stackoverflow.com/questions/58228533/issues-implementing-the-fang-algorithm-for-tdoa-trilateration

问题 I am having some trouble to find or implement an algorithm to find a signal source. The objective of my work is to find the sound emitter position. To accomplish this I am using three microfones. The technique that I am using is multilateration that is based on the time difference of arrival . The time difference of arrival between each microfones are found using Cross Correlation of the received signals. I already implemented the algorithm to find the time difference of arrival , but my

问题 I'm trying to implement a trilateration algorithm into my Android app to determine a user's indoor location. I'm using ultra-wideband beacons to get the distances to fixed points. I was able to adapt the method suggested in Trilateration Method Android Java as follows: public LatLng getLocationByTrilateration( LatLng location1, double distance1, LatLng location2, double distance2, LatLng location3, double distance3){ //DECLARE VARIABLES double[] P1 = new double[2]; double[] P2 = new double[2]

问题 I should be developing an indoor positioning system for some place , so I started by gathering info about how to develop such a system , the question I am up to now is : what controls the accuracy of positioning and how to improve it ? I found different APIs and projects with various accuracies , for example : ericsson indoor positioning API provides an accuracy within 10 meters , while Qubulus API provides an accuracy within 4 meters , and I met some projects like iDOCNET which claims to

问题 I should be developing an indoor positioning system for some place , so I started by gathering info about how to develop such a system , the question I am up to now is : what controls the accuracy of positioning and how to improve it ? I found different APIs and projects with various accuracies , for example : ericsson indoor positioning API provides an accuracy within 10 meters , while Qubulus API provides an accuracy within 4 meters , and I met some projects like iDOCNET which claims to

问题 I'm currently trying to develop a trilateration application to track beacons using 3 phones. I converted code I found in python over to c# but I'm having trouble getting it to work. This is my code: public double[] getPosition(double phoneADistance, double phoneBDistance, double phoneCDistance) { //meterToFeet is just a conversion method which takes the distance parameter and multiplies it by 3.28. double PhoneADist = meterToFeet(phoneADistance); double PhoneBDist = meterToFeet(phoneBDistance

问题 Assume that we have 4 points in 3-D (P1, P2, P3, P4). If the coordinates of those points are given with their euclidian distances to a fifth point P5 (r1, r2, r3, r4), how to calculate the coordinates of P5? In this post, answer of Don Reba is perfect for 2-D. But how do I extend it to 3-D? Here is my code for 2D: static void localize(double[] P1, double[] P2, double[] P3, double r1, double r2, double r3) { double[] ex = normalize(difference(P2, P1)); double i = dotProduct(ex, difference(P3,

问题 I am having some trouble to find or implement an algorithm to find a signal source. The objective of my work is to find the sound emitter position. To accomplish this I am using three vibration sensors. The technique that I am using is multilateration that is based on the time difference of arrival. The time difference of arrival between each sensor are found using Cross Correlation of the received signals. I already implemented the algorithm to find the time difference of arrival, but my