# -*- coding: utf-8 -*- """ Created on Fri Jul 18 23:23:08 2014 @author: rlabbe """ from math import radians, sin, cos, sqrt, exp import numpy.random as random import matplotlib.pyplot as plt import filterpy.kalman as kf import numpy as np def ball_kf(x, y, omega, v0, dt, r=0.5, q=0.02): g = 9.8 # gravitational constant f1 = kf.KalmanFilter(dim_x=5, dim_z=2) ay = .5*dt**2 f1.F = np.array ([[1, dt, 0, 0, 0], # x = x0+dx*dt [0, 1, 0, 0, 0], # dx = dx [0, 0, 1, dt, ay], # y = y0 +dy*dt+1/2*g*dt^2 [0, 0, 0, 1, dt], # dy = dy0 + ddy*dt [0, 0, 0, 0, 1]]) # ddy = -g. f1.H = np.array([ [1, 0, 0, 0, 0], [0, 0, 1, 0, 0]]) f1.R *= r f1.Q *= q omega = radians(omega) vx = cos(omega) * v0 vy = sin(omega) * v0 f1.x = np.array([[x,vx,y,vy,-9.8]]).T return f1 class BaseballPath(object): def __init__(self, x0, y0, launch_angle_deg, velocity_ms, noise=(1.0,1.0)): """ Create baseball path object in 2D (y=height above ground) x0,y0 initial position launch_angle_deg angle ball is travelling respective to ground plane velocity_ms speeed of ball in meters/second noise amount of noise to add to each reported position in (x,y) """ omega = radians(launch_angle_deg) self.v_x = velocity_ms * cos(omega) self.v_y = velocity_ms * sin(omega) self.x = x0 self.y = y0 self.noise = noise def drag_force (self, velocity): """ Returns the force on a baseball due to air drag at the specified velocity. Units are SI """ B_m = 0.0039 + 0.0058 / (1. + exp((velocity-35.)/5.)) return B_m * velocity def update(self, dt, vel_wind=0.): """ compute the ball position based on the specified time step and wind velocity. Returns (x,y) position tuple. """ # Euler equations for x and y self.x += self.v_x*dt self.y += self.v_y*dt # force due to air drag v_x_wind = self.v_x - vel_wind v = sqrt (v_x_wind**2 + self.v_y**2) F = self.drag_force(v) # Euler's equations for velocity self.v_x = self.v_x - F*v_x_wind*dt self.v_y = self.v_y - 9.81*dt - F*self.v_y*dt return (self.x + random.randn()*self.noise[0], self.y + random.randn()*self.noise[1]) def plot_ball(): y = 1. x = 0. theta = 35. # launch angle v0 = 50. dt = 1/10. # time step ball = BaseballPath(x0=x, y0=y, launch_angle_deg=theta, velocity_ms=v0, noise=[.3,.3]) f1 = ball_kf(x,y,theta,v0,dt,r=1.) f2 = ball_kf(x,y,theta,v0,dt,r=10.) t = 0 xs = [] ys = [] xs2 = [] ys2 = [] while f1.x[2,0] > 0: t += dt x,y = ball.update(dt) z = np.mat([[x,y]]).T f1.update(z) f2.update(z) xs.append(f1.x[0,0]) ys.append(f1.x[2,0]) xs2.append(f2.x[0,0]) ys2.append(f2.x[2,0]) f1.predict() f2.predict() p1 = plt.scatter(x, y, color='green', marker='o', s=75, alpha=0.5) p2, = plt.plot (xs, ys,lw=2) p3, = plt.plot (xs2, ys2,lw=4, c='r') plt.legend([p1,p2, p3], ['Measurements', 'Kalman filter(R=0.5)', 'Kalman filter(R=10)']) plt.show() def show_radar_chart(): plt.xlim([0.9,2.5]) plt.ylim([0.5,2.5]) plt.scatter ([1,2],[1,2]) #plt.scatter ([2],[1],marker='o') ax = plt.axes() ax.annotate('', xy=(2,2), xytext=(1,1), arrowprops=dict(arrowstyle='->', ec='r',shrinkA=3, shrinkB=4)) ax.annotate('', xy=(2,1), xytext=(1,1), arrowprops=dict(arrowstyle='->', ec='b',shrinkA=0, shrinkB=0)) ax.annotate('', xy=(2,2), xytext=(2,1), arrowprops=dict(arrowstyle='->', ec='b',shrinkA=0, shrinkB=4)) ax.annotate('Aircraft', xy=(2.04,2.), color='b') ax.annotate('altitude', xy=(2.04,1.5), color='k') ax.annotate('X', xy=(1.5, .9)) ax.annotate('Radar', xy=(.95, 0.9)) ax.annotate('Slant\n (r)', xy=(1.5,1.62), color='r') plt.title("Radar Tracking") ax.xaxis.set_ticklabels([]) ax.yaxis.set_ticklabels([]) ax.xaxis.set_ticks([]) ax.yaxis.set_ticks([]) plt.show() show_radar_chart()