我认为R中的一个算法版本仍然缺失:

gpsdistance<-function(lat1,lon1,lat2,lon2){

# internal function to change deg to rad

degreesToRadians<- function (degrees) {
return (degrees * pi / 180)
}

R<-6371e3  #radius of Earth in meters

phi1<-degreesToRadians(lat1) # latitude 1
phi2<-degreesToRadians(lat2) # latitude 2
lambda1<-degreesToRadians(lon1) # longitude 1
lambda2<-degreesToRadians(lon2) # longitude 2

delta_phi<-phi1-phi2 # latitude-distance
delta_lambda<-lambda1-lambda2 # longitude-distance

a<-sin(delta_phi/2)*sin(delta_phi/2)+
cos(phi1)*cos(phi2)*sin(delta_lambda/2)*
sin(delta_lambda/2)

cc<-2*atan2(sqrt(a),sqrt(1-a))

distance<- R * cc

return(distance)  # in meters
}

在SQL Server 2008中使用地理类型非常容易做到这一点。

SELECT geography::Point(lat1, lon1, 4326).STDistance(geography::Point(lat2, lon2, 4326))
-- computes distance in meters using eliptical model, accurate to the mm

4326是WGS84椭球地球模型的SRID

下面是Kotlin的一个变种:

import kotlin.math.*

class HaversineAlgorithm {

    companion object {
        private const val MEAN_EARTH_RADIUS = 6371.008
        private const val D2R = Math.PI / 180.0
    }

    private fun haversineInKm(lat1: Double, lon1: Double, lat2: Double, lon2: Double): Double {
        val lonDiff = (lon2 - lon1) * D2R
        val latDiff = (lat2 - lat1) * D2R
        val latSin = sin(latDiff / 2.0)
        val lonSin = sin(lonDiff / 2.0)
        val a = latSin * latSin + (cos(lat1 * D2R) * cos(lat2 * D2R) * lonSin * lonSin)
        val c = 2.0 * atan2(sqrt(a), sqrt(1.0 - a))
        return MEAN_EARTH_RADIUS * c
    }
}

寻找带谷歌的哈弗辛;以下是我的解决方案:

#include <math.h>
#include "haversine.h"

#define d2r (M_PI / 180.0)

//calculate haversine distance for linear distance
double haversine_km(double lat1, double long1, double lat2, double long2)
{
    double dlong = (long2 - long1) * d2r;
    double dlat = (lat2 - lat1) * d2r;
    double a = pow(sin(dlat/2.0), 2) + cos(lat1*d2r) * cos(lat2*d2r) * pow(sin(dlong/2.0), 2);
    double c = 2 * atan2(sqrt(a), sqrt(1-a));
    double d = 6367 * c;

    return d;
}

double haversine_mi(double lat1, double long1, double lat2, double long2)
{
    double dlong = (long2 - long1) * d2r;
    double dlat = (lat2 - lat1) * d2r;
    double a = pow(sin(dlat/2.0), 2) + cos(lat1*d2r) * cos(lat2*d2r) * pow(sin(dlong/2.0), 2);
    double c = 2 * atan2(sqrt(a), sqrt(1-a));
    double d = 3956 * c; 

    return d;
}

这取决于你需要它有多准确。如果你需要精确到毫米的精度，最好看看使用椭球的算法，而不是球体，比如Vincenty的算法。

打印稿版本

export const degreeToRadian = (degree: number) => {
  return degree * Math.PI / 180;
}

export const distanceBetweenEarthCoordinatesInKm = (lat1: number, lon1: number, lat2: number, lon2: number) => {
    const earthRadiusInKm = 6371;

    const dLat = degreeToRadian(lat2 - lat1);
    const dLon = degreeToRadian(lon2 - lon1);

    lat1 = degreeToRadian(lat1);
    lat2 = degreeToRadian(lat2);

    const a = Math.sin(dLat / 2) * Math.sin(dLat / 2) + Math.sin(dLon / 2) * Math.sin(dLon / 2) * Math.cos(lat1) * Math.cos(lat2);
    const c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1 - a));

    return earthRadiusInKm * c;
}