Radar blanking using dynamic subinterval noise floor estimation
View Patent ↗Techniques are provided for radar blanking using dynamic subinterval noise floor estimation. A radar blanking system implementing the techniques according to an embodiment includes a noise floor estimator configured to extract noise samples from a segment of in-phase (I) and quadrature (Q) input signal samples. The system also includes a blanking threshold calculator configured to calculate blanking thresholds based on statistics of the noise samples, the statistics including a mean of the noise samples and a standard deviation of the noise samples. The system further includes a blanking processor configured to select a subset of the IQ input signal samples that exceed the blanking thresholds and replace the selected subset of the IQ input signal samples with the mean of the noise samples to generate a blanked signal.
1 . A radar blanking system comprising:
a noise floor estimator configured to extract noise samples from a segment of in-phase (I) and quadrature (Q) input signal samples;
a blanking threshold calculator configured to calculate blanking thresholds based on statistics of the noise samples, the statistics including a mean of the noise samples and a standard deviation of the noise samples; and
a blanking processor configured to select a subset of the IQ input signal samples that exceed the blanking thresholds and replace the selected subset of the IQ input signal samples with the mean of the noise samples to generate a blanked signal.
2 . The system of claim 1 , wherein the noise floor estimator comprises:
a magnitude calculator configured to calculate magnitudes of the IQ input signal samples of the segment;
a sorting processor configured to sort the calculated magnitudes;
a noise threshold calculator configured to calculate a noise threshold based on a number, M, of smallest calculated magnitudes from the sorted calculated magnitudes; and
a noise sample selector configured to extract the noise samples from the segment based on a comparison of the calculated magnitudes to the noise threshold.
3 . The system of claim 1 , wherein the noise floor estimator comprises:
a magnitude calculator configured to calculate magnitudes of the IQ input signal samples of the segment;
a Rayleigh cumulative distribution (RCD) calculator configured to calculate a noise threshold based on the RCD of the calculated magnitudes; and
a noise sample selector configured to extract the noise samples from the segment based on a comparison of the calculated magnitudes to the noise threshold.
4 . The system of claim 1 , wherein the blanking threshold calculator is configured to calculate the blanking thresholds as an offset from the mean of the noise samples, the offset proportional to the standard deviation of the noise samples.
5 . The system of claim 1 , wherein the segment is a blanking duration interval of length N samples, and the blanking duration interval is based on a repetition interval of an interfering signal to be blanked.
6 . The system of claim 5 , wherein the noise floor estimator is configured to extract a number, M, of noise samples from the segment of IQ input signal samples, wherein M is a noise floor subinterval, and M is selected based on a duty cycle of the interfering signal.
7 . The system of claim 6 , wherein M is selected so that a ratio of M to N is in a range of 0.7 to 0.8.
8 . A computer program product including one or more non-transitory machine-readable mediums encoded with instructions that when executed by one or more processors cause a process to be carried out for radar blanking, the process comprising:
extracting noise samples from a segment of in-phase (I) and quadrature (Q) input signal samples;
calculating blanking thresholds based on statistics of the noise samples, the statistics including a mean of the noise samples and a standard deviation of the noise samples; and
selecting a subset of the IQ input signal samples that exceed the blanking thresholds and replacing the selected subset of the IQ input signal samples with the mean of the noise samples to generate a blanked signal.
9 . The computer program product of claim 8 , wherein the process comprises:
calculating magnitudes of the IQ input signal samples of the segment;
sorting the calculated magnitudes;
calculating a noise threshold based on a number, M, of smallest calculated magnitudes from the sorted calculated magnitudes; and
extracting the noise samples from the segment, based on a comparison of the calculated magnitudes to the noise threshold.
10 . The computer program product of claim 8 , wherein the process comprises:
calculating magnitudes of the IQ input signal samples of the segment;
calculating a noise threshold based on a Rayleigh cumulative distribution (RCD) of the calculated magnitudes; and
extracting the noise samples from the segment based on a comparison of the calculated magnitudes to the noise threshold.
11 . The computer program product of claim 8 , wherein the process comprises calculating the blanking thresholds as an offset from the mean of the noise samples, the offset proportional to the standard deviation of the noise samples.
12 . The computer program product of claim 8 , wherein the segment is a blanking duration interval of length N samples, and the blanking duration interval is based on a repetition interval of an interfering signal to be blanked.
13 . The computer program product of claim 12 , wherein a number, M, of the extracted noise samples from the segment of IQ input signal samples, is a noise floor subinterval, and M is selected based on a duty cycle of the interfering signal.
14 . The computer program product of claim 13 , wherein M is selected so that a ratio of M to N is in a range of 0.7 to 0.8.
15 . A method for radar blanking, the method comprising:
extracting noise samples from a segment of in-phase (I) and quadrature (Q) input signal samples;
calculating blanking thresholds based on statistics of the noise samples, the statistics including a mean of the noise samples and a standard deviation of the noise samples; and
selecting a subset of the IQ input signal samples that exceed the blanking thresholds and replacing the selected subset of the IQ input signal samples with the mean of the noise samples to generate a blanked signal.
16 . The method of claim 15 , comprising:
calculating magnitudes of the IQ input signal samples of the segment;
sorting the calculated magnitudes;
calculating a noise threshold based on a number, M, of smallest calculated magnitudes from the sorted calculated magnitudes; and
extracting the noise samples from the segment, based on a comparison of the calculated magnitudes to the noise threshold.
17 . The method of claim 15 , comprising:
calculating magnitudes of the IQ input signal samples of the segment;
calculating a noise threshold based on a Rayleigh cumulative distribution (RCD) of the calculated magnitudes; and
extracting the noise samples from the segment based on a comparison of the calculated magnitudes to the noise threshold.
18 . The method of claim 15 , wherein the process comprises calculating the blanking thresholds as an offset from the mean of the noise samples, the offset proportional to the standard deviation of the noise samples.
19 . The method of claim 15 , wherein the segment is a blanking duration interval of length N samples, and the blanking duration interval is based on a repetition interval of an interfering signal to be blanked.
20 . The method of claim 19 , wherein a number, M, of the extracted noise samples from the segment of IQ input signal samples, is a noise floor subinterval, and M is selected based on a duty cycle of the interfering signal.