freqz数字滤波器的频率响应(幅频特性与相频特性)

东方耀

数字滤波器的频率响应(幅频特性与相频特性)

freqz 明白了 0-2*pi 那个是  归一化的数字域频率

1. # -*- coding: utf-8 -*-
   
2. __author__ = u'东方耀 微信：dfy_88888'
   
3. __date__ = '2022/9/1 上午8:57'
   
4. __product__ = 'PyCharm'
   
5. __filename__ = '25_BPSK调制解调物理层仿真'
   
6. 
   
7. 
   
8. from common.radar_common import *
   
9. 
   
10. # 选择Mark Directory as,然后选择第一项：Sources Root   红线消失
    
11. 
    
12. # pip3 install scikit-commpy   https://github.com/veeresht/CommPy
    
13. # https://blog.51cto.com/u_15127585/2670058
    
14. 
    
15. from commpy.filters import rcosfilter, rrcosfilter
    
16. 
    
17. 
    
18. mat_file = "/home/jiang/matlab_works/zhihu_tongxin/h1.mat"
    
19. 
    
20. mat_data = scio.loadmat(mat_file)
    
21. print("matlab数据的字典keys=", mat_data.keys())
    
22. 
    
23. 
    
24. bit_rate = 1000  # 比特率
    
25. symbol_rate = 1000 # 符号率
    
26. sps = 16 #每个符号的采样点数
    
27. fc = 2000 #载波频率
    
28. fs = 16000 #采样频率 = sps * symbol_rate
    
29. sample_num = 129
    
30. Roll_off_factor = 0.6
    
31. 
    
32. time_idx, h_rc = rcosfilter(sample_num, Roll_off_factor, Ts=1/symbol_rate, Fs=fs)
    
33. h1 = mat_data["h1"][0]
    
34. # -1 1 2*fs  sinc怎么取 没懂
    
35. h_sinc = np.sinc(np.linspace(-4, 4, sample_num))
    
36. 
    
37. 
    
38. print("时刻(间隔是采样间隔,非符合间隔):", len(time_idx), time_idx[1] - time_idx[0], 1/symbol_rate, 1/fs, time_idx[:10])
    
39. print("滤波器幅值:", len(h_rc), h_rc[:5])
    
40. 
    
41. # Compute the frequency response of a digital filter 数字滤波器的频率响应
    
42. # `w` is normalized to the range [0, pi) (radians/sample)
    
43. # The frequency response, as complex numbers
    
44. # https://vimsky.com/examples/usage/python-scipy.signal.freqz.html
    
45. w, frequency_response = signal.freqz(h_sinc, a=1)
    
46. 
    
47. 
    
48. fig = plt.figure(figsize=(18, 20))  # H=2000  W=1800像素
    
49. plt.figure(1)
    
50. plt.subplots_adjust(wspace=0, hspace=0.4)
    
51. plt.subplot(2, 1, 1)
    
52. plt.xlabel("采样点/时刻",
    
53.            fontproperties=font, fontsize=15)
    
54. plt.ylabel("幅值", fontproperties=font, fontsize=15)
    
55. 
    
56. plt.plot(time_idx, h_sinc, marker='o', markersize=4,
    
57.              markerfacecolor=my_color[0], color=my_color[0], label="sinc")
    
58. plt.plot(time_idx, h_rc, marker='o', markersize=4,
    
59.              markerfacecolor=my_color[1], color=my_color[1], label="python")
    
60. plt.plot(time_idx, h1, marker='o', markersize=4,
    
61.              markerfacecolor=my_color[2], color=my_color[2], label="matlab")
    
62. plt.legend(loc="best")
    
63. plt.title('rcosfilter升余弦滚降滤波器(滚降因子beta=%.1f)对比' % Roll_off_factor,
    
64.              fontproperties=font, fontsize=18)
    
65. 
    
66. plt.subplot(2, 1, 2)
    
67. plt.plot(w/np.pi, 20 * np.log10(np.abs(frequency_response)), marker='o', markersize=4,
    
68.              markerfacecolor=my_color[3], color=my_color[3], label="Amplitude-frequency")
    
69. # plt.plot(w, np.unwrap(np.angle(h)), 'g')
    
70. plt.plot(w/np.pi, np.unwrap(np.angle(frequency_response)), marker='o', markersize=4,
    
71.              markerfacecolor=my_color[4], color=my_color[4], label="Phase-frequency")
    
72. plt.xlabel("归一化的频率(*pi radians/sample)",
    
73.            fontproperties=font, fontsize=15)
    
74. plt.ylabel("幅值(db)", fontproperties=font, fontsize=15)
    
75. plt.legend(loc="best")
    
76. 
    
77. plt.title('数字滤波器的频率响应(幅频特性与相频特性)',
    
78.              fontproperties=font, fontsize=18)
    
79. 
    
80. plt.show()
    
81. 
    
82. 
    
83. 
    
84. 
    

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