定位原理很简单，故不赘述，直接上源码，内附注释。（如果对您的学习有所帮助，还请帮忙点个赞，谢谢了）

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed May 16 10:50:29 2018@author: dag
"""
import sympy
import numpy as np
import math
from matplotlib.pyplot import plot
from matplotlib.pyplot import show
import matplotlib.pyplot as plt
import matplotlib
#解决无法显示中文问题，fname是加载字体路径，根据自身pc实际确定，具体请百度
zhfont1 = matplotlib.font_manager.FontProperties(fname='/System/Library/Fonts/Hiragino Sans GB W3.ttc')#随机产生3个参考节点坐标
maxy = 1000
maxx = 1000
cx = maxx*np.random.rand(3)
cy = maxy*np.random.rand(3)
dot1 = plot(cx,cy,'k^')#生成盲节点，以及其与参考节点欧式距离
mtx = maxx*np.random.rand()
mty = maxy*np.random.rand()
plt.hold('on')
dot2 = plot(mtx,mty,'go')
da = math.sqrt(np.square(mtx-cx[0])+np.square(mty-cy[0]))
db = math.sqrt(np.square(mtx-cx[1])+np.square(mty-cy[1])) 
dc = math.sqrt(np.square(mtx-cx[2])+np.square(mty-cy[2]))#计算定位坐标  
def triposition(xa,ya,da,xb,yb,db,xc,yc,dc): x,y = sympy.symbols('x y')f1 = 2*x*(xa-xc)+np.square(xc)-np.square(xa)+2*y*(ya-yc)+np.square(yc)-np.square(ya)-(np.square(dc)-np.square(da))f2 = 2*x*(xb-xc)+np.square(xc)-np.square(xb)+2*y*(yb-yc)+np.square(yc)-np.square(yb)-(np.square(dc)-np.square(db))result = sympy.solve([f1,f2],[x,y])locx,locy = result[x],result[y]return [locx,locy]#解算得到定位节点坐标
[locx,locy] = triposition(cx[0],cy[0],da,cx[1],cy[1],db,cx[2],cy[2],dc)
plt.hold('on')
dot3 = plot(locx,locy,'r*')#显示脚注
x = [[locx,cx[0]],[locx,cx[1]],[locx,cx[2]]]
y = [[locy,cy[0]],[locy,cy[1]],[locy,cy[2]]]
for i in range(len(x)):plt.plot(x[i],y[i],linestyle = '--',color ='g' )
plt.title('三边测量法的定位',fontproperties=zhfont1)  
plt.legend(['参考节点','盲节点','定位节点'], loc='lower right',prop=zhfont1)
show() 
derror = math.sqrt(np.square(locx-mtx) + np.square(locy-mty)) 
print(derror) 

输出效果图：