如何计算两个GPS坐标之间的距离(使用经纬度)?
当前回答
这段Lua代码改编自维基百科和Robert Lipe的GPSbabel工具:
local EARTH_RAD = 6378137.0
-- earth's radius in meters (official geoid datum, not 20,000km / pi)
local radmiles = EARTH_RAD*100.0/2.54/12.0/5280.0;
-- earth's radius in miles
local multipliers = {
radians = 1, miles = radmiles, mi = radmiles, feet = radmiles * 5280,
meters = EARTH_RAD, m = EARTH_RAD, km = EARTH_RAD / 1000,
degrees = 360 / (2 * math.pi), min = 60 * 360 / (2 * math.pi)
}
function gcdist(pt1, pt2, units) -- return distance in radians or given units
--- this formula works best for points close together or antipodal
--- rounding error strikes when distance is one-quarter Earth's circumference
--- (ref: wikipedia Great-circle distance)
if not pt1.radians then pt1 = rad(pt1) end
if not pt2.radians then pt2 = rad(pt2) end
local sdlat = sin((pt1.lat - pt2.lat) / 2.0);
local sdlon = sin((pt1.lon - pt2.lon) / 2.0);
local res = sqrt(sdlat * sdlat + cos(pt1.lat) * cos(pt2.lat) * sdlon * sdlon);
res = res > 1 and 1 or res < -1 and -1 or res
res = 2 * asin(res);
if units then return res * assert(multipliers[units])
else return res
end
end
其他回答
下面是我在Python中使用的Haversine函数:
from math import pi,sqrt,sin,cos,atan2
def haversine(pos1, pos2):
lat1 = float(pos1['lat'])
long1 = float(pos1['long'])
lat2 = float(pos2['lat'])
long2 = float(pos2['long'])
degree_to_rad = float(pi / 180.0)
d_lat = (lat2 - lat1) * degree_to_rad
d_long = (long2 - long1) * degree_to_rad
a = pow(sin(d_lat / 2), 2) + cos(lat1 * degree_to_rad) * cos(lat2 * degree_to_rad) * pow(sin(d_long / 2), 2)
c = 2 * atan2(sqrt(a), sqrt(1 - a))
km = 6367 * c
mi = 3956 * c
return {"km":km, "miles":mi}
下面是c#语言(用纬度和弧度表示):
double CalculateGreatCircleDistance(double lat1, double long1, double lat2, double long2, double radius)
{
return radius * Math.Acos(
Math.Sin(lat1) * Math.Sin(lat2)
+ Math.Cos(lat1) * Math.Cos(lat2) * Math.Cos(long2 - long1));
}
如果你的纬度和长度是用角度表示的,那么除以180/PI就可以转换成弧度。
在我的项目中,我需要计算很多点之间的距离,所以我继续尝试优化我在这里找到的代码。平均而言,在不同的浏览器中,我的新实现的运行速度比获得最多好评的答案快2倍。
function distance(lat1, lon1, lat2, lon2) {
var p = 0.017453292519943295; // Math.PI / 180
var c = Math.cos;
var a = 0.5 - c((lat2 - lat1) * p)/2 +
c(lat1 * p) * c(lat2 * p) *
(1 - c((lon2 - lon1) * p))/2;
return 12742 * Math.asin(Math.sqrt(a)); // 2 * R; R = 6371 km
}
您可以在这里使用我的jsPerf并查看结果。
最近我需要在python中做同样的事情,所以这里是一个python实现:
from math import cos, asin, sqrt
def distance(lat1, lon1, lat2, lon2):
p = 0.017453292519943295
a = 0.5 - cos((lat2 - lat1) * p)/2 + cos(lat1 * p) * cos(lat2 * p) * (1 - cos((lon2 - lon1) * p)) / 2
return 12742 * asin(sqrt(a))
为了完整起见:维基上的Haversine。
你可以在f#的fssnip中找到这个实现(有一些很好的解释)
以下是重要的部分:
let GreatCircleDistance<[<Measure>] 'u> (R : float<'u>) (p1 : Location) (p2 : Location) =
let degToRad (x : float<deg>) = System.Math.PI * x / 180.0<deg/rad>
let sq x = x * x
// take the sin of the half and square the result
let sinSqHf (a : float<rad>) = (System.Math.Sin >> sq) (a / 2.0<rad>)
let cos (a : float<deg>) = System.Math.Cos (degToRad a / 1.0<rad>)
let dLat = (p2.Latitude - p1.Latitude) |> degToRad
let dLon = (p2.Longitude - p1.Longitude) |> degToRad
let a = sinSqHf dLat + cos p1.Latitude * cos p2.Latitude * sinSqHf dLon
let c = 2.0 * System.Math.Atan2(System.Math.Sqrt(a), System.Math.Sqrt(1.0-a))
R * 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;
}