Modulation feature measurement and statistical classification system and method

• US 20060239338A1
• Filed: 02/15/2006
• Published: 10/26/2006
• Est. Priority Date: 02/15/2005
• Status: Abandoned Application

• Current Assignee: Sierra Nevada Corporation
• Original Assignee: Sierra Nevada Corporation
• Inventors: Carlsen, Eric C., Polakowski, Michael A., Kolanek, James
• Application Number:
  US11/354,632
• Publication Number:
  US 20060239338A1
• Time in Patent Office: Days
• US Class Current: 375/224
• CPC Class Codes: H04L 27/0012 arrangements for identifying the type of modulation

Abstract

A modulation feature measurement and classification system for classifying a pulsed signal that includes a preprocessor, phase measurement system and modulation classifier. Preprocessor detects pulse starts and stops, measures pulse duration and converts the pulsed signal into digitized baseband in-phase/quadrature samples. Phase measurement system measures short chip counts, long chip counts, phase jump magnitudes, number of phase states, and polynomial coefficients for phase modulation of the pulsed signal. Modulation classifier determines modulation type based on the measurements using both rules-based and similarity-based classification methods.

Claims

1. A modulation feature measurement and classification system for classifying a pulsed signal, the modulation feature measurement and classification system comprising:

a preprocessor that detects a pulse start and a pulse stop, and that measures pulse duration for the pulsed signal and that converts the pulsed signal into a plurality of digitized baseband in-phase/quadrature samples;

a phase measurement system that measures short chip counts, long chip counts, phase jump magnitudes, number of phase states, and phase modulation polynomial coefficients for a curve fit to a phase waveform for the pulsed signal; and

a modulation classifier that determines a modulation type of the pulsed signal based on the measurements of the preprocessor and the phase measurement system using both rules-based and similarity-based classification methods.

2. The modulation feature measurement and classification system of claim 1, wherein the modulation classifier uses both rule-based and similarity-based classification methods to classify the modulation type of the pulsed signal.

3. The modulation feature measurement and classification system of claim 1, wherein the modulation classifier classifies the pulsed signal as having phase shift keyed modulation if the phase jump magnitude exceeds π

/2.

4. The modulation feature measurement and classification system of claim 1, wherein the modulation classifier uses Mahalanobis distance for the similarity-based classification methods.

5. The modulation feature measurement and classification system of claim 1, wherein the phase measurement system comprises:

a coordinate rotation digital computer for converting the plurality of digitized baseband in-phase/quadrature samples into a plurality of amplitude and phase samples;

a phase jump detector for measuring a phase jump magnitude between consecutive phase samples and detecting when the phase jump magnitude exceeds a phase jump threshold;

a phase jump counter for counting the number of consecutive times the phase jump magnitude exceeds the phase jump threshold, the phase jump counter resetting when the phase jump magnitude fails to exceed the phase jump threshold;

a chip counter for measuring the short chip counts and the long chip counts;

a phase state counter for determining the number of phase states from the phase jump magnitude measurements made by the phase jump detector; and

a processor for determining the phase modulation polynomial coefficients.

6. The modulation feature measurement and classification system of claim 5, wherein the phase state counter determines the number of phase states using a clustering method with a threshold distance measure.

7. The modulation feature measurement and classification system of claim 5, wherein the phase measurement system further comprises:

a frequency discriminator that performs a difference operation with a programmable delay on the plurality of phase samples from the coordinate rotation digital computer; and

an anti-wrap circuit that removes a carrier frequency bias and large spikes due to phase wraps from the output of the frequency discriminator.

8. The modulation feature measurement and classification system of claim 7, wherein the preprocessor generates a start event signal when detecting a pulse leading edge and generates a stop event signal when detecting a pulse trailing edge, the start event signal being sent to the anti-wrap circuit and the chip counter, and the stop event signal being sent to the chip counter.

9. The modulation feature measurement and classification system of claim 8, wherein the chip counter uses a short chip count threshold and a long chip count threshold, the short chip count threshold being equal to the programmable delay of the frequency discriminator.

10. The modulation feature measurement and classification system of claim 5, wherein the processor for determining the phase modulation polynomial coefficients uses a least squares method to fit a K-th order polynomial of the form:

$b<br><br>\left(n\right)=c_0+c_1<br><br>\frac{2<br><br>\left(n-n_0\right)}{N}+c_2<br><br>\frac{2^2<br><br>{\left(n-n_0\right)}^2}{N^2}+\mathrm{\dots <br><br>}+c_K<br><br>\frac{2^K<br><br>{\left(n-n_0\right)}^K}{N^K}$

to the phase waveform of the input signal, where n₀ is the midpoint of the waveform, N is the total number of samples, and the c_i are the desired polynomial coefficients.

11. A rule and distance based method for classifying the modulation of a pulsed signal, comprising:

accepting measurements of pulse duration, short chip count, long chip count, phase jump magnitude, number of phase states and phase modulation polynomial coefficients for the pulsed signal;

classifying the pulsed signal as having phase-shift keyed modulation if the maximum phase jump magnitude is greater than π

/2;

if the pulsed signal is classified as having phase-shift keyed modulation, determining whether the long chip count is greater than zero;

if the pulsed signal is classified as having phase-shift keyed modulation and the long chip count is greater than zero, classifying the pulsed signal as having segmented modulation;

if the pulsed signal is classified as having phase-shift keyed modulation and the long chip count is zero, determining whether the number of phases states is greater than two;

if the pulsed signal is classified as having phase-shift keyed modulation, the long chip count is zero, and the number of phases states is not greater than two, classifying the pulsed signal as having binary phase-shift keyed modulation;

if the pulsed signal is classified as having phase-shift keyed modulation, the long chip count is zero, and the number of phases states is greater than two, classifying the pulsed signal as having multiple phase-shift keyed modulation;

if the pulsed signal is not classified as having phase-shift keyed modulation, determining whether the pulse duration is less than about 0.8 microseconds;

if the pulsed signal is not classified as having phase-shift keyed modulation and the pulse duration is less than about 0.8 microseconds, classifying the pulsed signal as having no pulse modulation; and

if the pulsed signal is not classified as having phase-shift keyed modulation and the pulse duration is not less than about 0.8 microseconds, using the number of phase states to classify the modulation of the pulsed signal.

12. The method of claim 11, wherein the step of classifying the pulsed signal as having binary phase-shift keyed modulation comprises:

using the short chip count to determine the type of binary phase-shift keyed modulation;

classifying the pulsed signal as having Barker coded binary phase-shift keyed modulation if the short chip count is 2, 3, 5 or 6;

classifying the pulsed signal as having maximum length pseudorandom noise modulation if the short chip count is 2″

or 2″

−

1, where n≧

6;

classifying the pulsed signal as having combined Barker coded binary phase-shift keyed modulation if the short chip count is 4, 7, 9, 10, 12, 13, 14, 16, 17, 19, 21, 22, 24, 25, 26, 27, 32, 38, 45, 60, 71, or 84; and

otherwise classifying the pulsed signal as having other binary phase-shift keyed modulation.

13. The method of claim 11, wherein the step of classifying the pulsed signal as having multiple phase-shift keyed modulation comprises:

utilizing a distance-based method to determine the type of multiple phase-shift keyed modulation based on the phase modulation polynomial coefficients of the pulsed signal and parameters for different multiple phase-shift keyed modulation types.

14. The method of claim 13, wherein the distance-based method is the Mahalanobis classifier, and the parameters for different multiple phase-shift keyed modulation types are the mean value vectors and sample covariance matrices of the polynomial fit phase coefficients for the different multiple phase-shift keyed modulation types.

15. The method of claim 14, further comprising calculating a confidence level for the classification of the type of multiple phase-shift keyed modulation.

16. The method of claim 11, wherein the step of using the number of phase states to classify the modulation of the pulsed signal, if the pulsed signal is not classified as having phase-shift keyed modulation and the pulse duration is not less than about 0.8 microseconds, comprises:

further classifying the pulsed signal as having frequency-shift keyed modulation if the number of phase states is greater than 1;

further classifying the pulsed signal as having one of frequency-shift keyed modulation, linear frequency modulation, or non-linear frequency modulation if the number of phase states is equal to 1; and

further classifying the pulsed signal as having one of frequency-shift keyed modulation, linear frequency modulation, non-linear frequency modulation, or no modulation if the number of phase states is equal to 0.

17. The method of claim 16, wherein each of the steps of further classifying the pulsed signal comprises:

utilizing a distance-based method to determine the type of modulation based on the phase modulation polynomial coefficients of the pulsed signal and parameters for the different possible modulation classifications for a pulsed signal with the number of phase states.

18. The method of claim 17, wherein the distance-based method is the Mahalanobis classifier, and the step of further classifying the pulsed signal as having frequency-shift keyed modulation further comprises:

assigning the pulsed signal as having one of linear stepped frequency modulation or Taylor quadraphase modulation utilizing the Mahalanobis classifier;

calculating a confidence level for the assignment;

if the confidence level is less than 0.95 and the pulsed signal is assigned as having linear stepped frequency modulation, reassigning the pulsed signal as having random stepped frequency modulation/other frequency-shift keyed modulation; and

if the confidence level is less than 0.95 and the pulsed signal is assigned as having Taylor quadraphase modulation, reassigning the pulsed signal as having random stepped frequency modulation/other frequency-shift keyed modulation.

19. The method of claim 17, wherein the distance-based method is the Mahalanobis classifier, and the step of further classifying the pulsed signal as having one of frequency-shift keyed modulation, linear frequency modulation, or non-linear frequency modulation further comprises:

assigning the pulsed signal as having one of linear stepped frequency modulation, Taylor quadraphase, linear frequency modulation, non-linear frequency modulation, up/down linear frequency modulation or up/down non-linear frequency modulation utilizing the Mahalanobis classifier;

calculating a confidence level for the assignment;

if the confidence level is less than 0.95 and the pulsed signal is assigned as having linear stepped frequency modulation, reassigning the pulsed signal as having random stepped frequency modulation/other frequency-shift keyed modulation; and

if the confidence level is less than 0.95 and the pulsed signal is assigned as having Taylor quadraphase modulation, reassigning the pulsed signal as having random stepped frequency modulation/other frequency-shift keyed modulation.

20. The method of claim 17, wherein the distance-based method is the Mahalanobis classifier, and the step of further classifying the pulsed signal as having one of frequency-shift keyed modulation, linear frequency modulation, non-linear frequency modulation, or no modulation, comprises:

assigning the pulsed signal as having one of linear stepped frequency modulation, Taylor quadraphase, linear frequency modulation, non-linear frequency modulation, up/down linear frequency modulation, up/down non-linear frequency modulation, or no modulation utilizing the Mahalanobis classifier;

calculating a confidence level for the assignment;

if the confidence level is less than 0.95 and the pulsed signal is assigned as having linear stepped frequency modulation, reassigning the pulsed signal as having random stepped frequency modulation/other frequency-shift keyed modulation; and

if the confidence level is less than 0.95 and the pulsed signal is assigned as having Taylor quadraphase modulation, reassigning the pulsed signal as having random stepped frequency modulation/other frequency-shift keyed modulation.