我尝试使用我的USRP E100捕获GPS信号并将其保存到.bin文件中,并使用GNU Radio Companion实现以下流程图:
正如您所看到的,我从GPS频率接收了50M复杂样本,我采用了它们的实部和虚部。然后,我进行Float to Char转换,并将其保存为IQIQIQIQ(...)bin文件。如果没有Float to Char转换,一切都运行良好,但如果有,则输出文件仅填充0(例如浮点输出" b502 323a b502 32b8 b502 b239 1d12 0b3a"转换为字符输出" 0000 0000 0000 0000 0000 0000 0000 0000")。
我不知道这里发生了什么,因为如果使用了Float to Char块,则会出现错误。我也尝试使用其他类型的转换器,例如Float to Short,我得到相同的输出:0的矢量。
生成流程图时生成的代码如下所示:
#!/usr/bin/env python
##################################################
# Gnuradio Python Flow Graph
# Title: Gps Datagrabber
# Generated: Wed Feb 3 10:01:35 2016
##################################################
from gnuradio import eng_notation
from gnuradio import gr
from gnuradio import uhd
from gnuradio.eng_option import eng_option
from gnuradio.gr import firdes
from optparse import OptionParser
class GPS_datagrabber(gr.top_block):
def __init__(self):
gr.top_block.__init__(self, "Gps Datagrabber")
##################################################
# Variables
##################################################
self.samp_rate = samp_rate = 5*1000000
self.Tiempo_sec = Tiempo_sec = 10
self.gain = gain = 15
self.center_freq = center_freq = int(1.57542e9)
self.band = band = int(40e6)
self.Samples = Samples = Tiempo_sec*samp_rate
##################################################
# Blocks
##################################################
self.gr_interleave_0 = gr.interleave(gr.sizeof_char*1)
self.gr_head_0 = gr.head(gr.sizeof_gr_complex*1, 50000000)
self.gr_float_to_char_1 = gr.float_to_char()
self.gr_float_to_char_0 = gr.float_to_char()
self.gr_file_sink_0 = gr.file_sink(gr.sizeof_char*1, "/home/root/Desktop/USRP_E100")
self.gr_file_sink_0.set_unbuffered(True)
self.gr_complex_to_real_0 = gr.complex_to_real(1)
self.gr_complex_to_imag_0 = gr.complex_to_imag(1)
self.USRP_sync_123 = uhd.usrp_source(
device_addr="addr0=192.168.10.1",
stream_args=uhd.stream_args(
cpu_format="fc32",
channels=range(1),
),
)
self.USRP_sync_123.set_clock_source("external", 0)
self.USRP_sync_123.set_time_source("external", 0)
self.USRP_sync_123.set_samp_rate(samp_rate)
self.USRP_sync_123.set_center_freq(center_freq, 0)
self.USRP_sync_123.set_gain(gain, 0)
self.USRP_sync_123.set_antenna("TX/RX", 0)
self.USRP_sync_123.set_bandwidth(band, 0)
##################################################
# Connections
##################################################
self.connect((self.USRP_sync_123, 0), (self.gr_head_0, 0))
self.connect((self.gr_head_0, 0), (self.gr_complex_to_real_0, 0))
self.connect((self.gr_interleave_0, 0), (self.gr_file_sink_0, 0))
self.connect((self.gr_complex_to_real_0, 0), (self.gr_float_to_char_0, 0))
self.connect((self.gr_float_to_char_0, 0), (self.gr_interleave_0, 0))
self.connect((self.gr_complex_to_imag_0, 0), (self.gr_float_to_char_1, 0))
self.connect((self.gr_float_to_char_1, 0), (self.gr_interleave_0, 1))
self.connect((self.gr_head_0, 0), (self.gr_complex_to_imag_0, 0))
def get_samp_rate(self):
return self.samp_rate
def set_samp_rate(self, samp_rate):
self.samp_rate = samp_rate
self.set_Samples(self.Tiempo_sec*self.samp_rate)
self.USRP_sync_123.set_samp_rate(self.samp_rate)
def get_Tiempo_sec(self):
return self.Tiempo_sec
def set_Tiempo_sec(self, Tiempo_sec):
self.Tiempo_sec = Tiempo_sec
self.set_Samples(self.Tiempo_sec*self.samp_rate)
def get_gain(self):
return self.gain
def set_gain(self, gain):
self.gain = gain
self.USRP_sync_123.set_gain(self.gain, 0)
self.USRP_sync_123.set_gain(self.gain, 1)
self.USRP_sync_123.set_gain(self.gain, 2)
def get_center_freq(self):
return self.center_freq
def set_center_freq(self, center_freq):
self.center_freq = center_freq
self.USRP_sync_123.set_center_freq(self.center_freq, 0)
self.USRP_sync_123.set_center_freq(self.center_freq, 1)
self.USRP_sync_123.set_center_freq(self.center_freq, 2)
def get_band(self):
return self.band
def set_band(self, band):
self.band = band
self.USRP_sync_123.set_bandwidth(self.band, 0)
self.USRP_sync_123.set_bandwidth(self.band, 1)
self.USRP_sync_123.set_bandwidth(self.band, 2)
def get_Samples(self):
return self.Samples
def set_Samples(self, Samples):
self.Samples = Samples
if __name__ == '__main__':
parser = OptionParser(option_class=eng_option, usage="%prog: [options]")
(options, args) = parser.parse_args()
tb = GPS_datagrabber()
tb.run()
错误在哪里?也许是USRP /硬件问题?或者我可能无法将Float数据转换为Char数据?
答案 0 :(得分:3)
当以复数运算时,默认情况下USRP会将每个IQ样本缩放到[-1,1]范围内。
但是,我认为输入信号可能非常弱,因此每个IQ样本值应低于[-0.5,0.5]。 Float to Char
块执行从float到char的转换。但是将浮点数转换为[-0.5,0.5]范围内的整数应始终为零。这就是为什么你的文件只包含零。
为了避免此问题,有两种可能的解决方案:
解决方案1:
正确缩放传入的IQ样本,使其范围超出[-0.5,0.5]范围。这可以通过将信号乘以常数或正确更改Scale
块的Float to Char
参数来完成。
解决方案2:
由于您对8位采样精度感兴趣,我建议指示USRP以流签图的符号短(16位)格式传递样本。每个IQ样本的范围将在[-2 ^ 15,2 ^ 15]。然后只执行Short to Char
转换,但要确保每个样本的幅度不大于2 ^ 7,否则您将获得剪切效果。使用此解决方案,流程图中流动的数据要少得多,因为每个IQ样本都具有与复杂形式相比的一半大小。此外,整数下降更快。