METHODS AND APPARATUS FOR DETECTION/CLASSIFICATION OF RADAR TARGETS INCLUDING BIRDS AND OTHER HAZARDS

• US 20100079328A1
• Filed: 05/05/2009
• Published: 04/01/2010
• Est. Priority Date: 05/05/2008
• Status: Active Grant

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Raytheon Company (Rtx Corporation)
• Inventors: Lok, Yochoi F., Drake, Peter R.
• Granted Patent: US 7,948,429 B2
• Time in Patent Office: Days
• US Class Current: 342/36
• CPC Class Codes: G01S 13/424 Stacked beam radar
• CPC Class Codes: G01S 7/024 using polarisation effects in waveguides H01P1/165; for aerials H01Q, e.g. H01Q15/22, H01Q15/24, H01Q19/195
• CPC Class Codes: G01S 7/411 Identification of targets based on measurements of radar reflectivity G01S7/415 takes precedence
• CPC Class Codes: G01S 7/412 based on a comparison between measured values and known or stored values
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

Methods and apparatus for processing data from a low beam channel, a high beam channel and a weather channel to perform an altitude estimation based upon a target amplitude ratio between the low beam channel and the high beam channel and target range, and for performing target detection based upon data from the weather channel. In one embodiment, migrating birds can be more accurately detected and classified than with conventional systems.

Claims

1. A system, comprising:

an antenna;

a target channel including;

a low beam receiver channel;

a high beam receiver channel; and

a weather receiver channel; and

a signal processor to receive data from the low beam channel, the high beam channel and the weather channel for performing an altitude estimation based upon a target amplitude ratio between the low beam channel and the high beam channel and target range, and for performing target classification by calculating polarimetric parameters from the target data and the weather data including differential reflectivity and differential phase data, wherein the target channel has a different polarization than the weather channel.

2. The system according to claim 1, wherein the altitude estimation is obtained and altitude accuracy is obtained by smoothing over multiple scans.

3. The system according to claim 1, wherein the differential reflectivity and the differential phase are obtained from co-polarization data and reverse polarization data.

4. The system according to claim 1, wherein the signal processor generates probability values for a target.

5. The system according to claim 4, wherein the probability values correspond to at least birds and aircraft.

6. The system according to claim 1, wherein the differential reflectivity is defined as:

$Z_{\mathrm{DR}}=10·<br><br>{\log }_{10}<br><br>\left(\frac{I_c^2+Q_c^2}{I_r^2+Q_r^2}\right),$

and the differential phase is defined as;

${\mathrm{\phi <br><br>}}_{\mathrm{DR}}={\tan }^{-1}<br><br>\left(\frac{I_c}{Q_c}\right)-{\tan }^{-1}<br><br>\left(\frac{I_r}{Q_r}\right),$

where R is range, I_c and Q_c are the in-phase and quadrature data of the co-polarization channel, and I_r and Q_r are the in-phase and quadrature data of the reverse polarization channel.

7. The system according to claim 1, wherein the weather channel data and the target channel data are processed in the same radar dwell for simultaneous polarimetric data.

8. A method, comprising:

receiving radar return at a target channel and a weather channel, wherein the target channel includes a low beam receiver channel and a high beam receiver channel;

transforming the radar return in a signal processor and memory including processing data from the low beam channel, the high beam channel and the weather channel to generate altitude estimation data based upon a target amplitude ratio between the low beam channel and the high beam channel and target range; and

transforming the radar return comprising performing target classification by calculating polarimetric parameters from the target data and the weather data including differential reflectivity and differential phase data, wherein the target channel has a different polarization than the weather channel.

9. The method according to claim 8, wherein the altitude estimation is obtained and improved altitude accuracy is obtained by smoothing over multiple scans.

10. The method according to claim 8, wherein the differential reflectivity and the differential phase are obtained from co-polarization data and reverse polarization data.

11. The method according to claim 8, further including generating probability values for a target.

12. The method according to claim 11, wherein the probability values correspond to at least birds and aircraft.

13. The method according to claim 8, wherein the differential reflectivity is defined as:

$Z_{\mathrm{DR}}=10·<br><br>{\log }_{10}\left(\frac{I_c^2+Q_c^2}{I_r^2+Q_r^2}\right),$

and the differential phase is defined as;

${\mathrm{\phi <br><br>}}_{\mathrm{DR}}={\tan }^{-1}<br><br>\left(\frac{I_c}{Q_c}\right)-{\tan }^{-1}<br><br>\left(\frac{I_r}{Q_r}\right),$

where R is range, I_c and Q_c are the in-phase and quadrature data of the co-polarization channel, and I_r and Q_r are the in-phase and quadrature data of the reverse polarization channel.

14. An article, comprising:

a computer readable medium comprising stored instructions that enable a machine to perform the steps of;

receiving radar return at a target channel and a weather channel, wherein the target channel includes a low beam receiver channel and a high beam receiver channel;

transforming the radar return in a signal processor and memory including processing data from the low beam channel, the high beam channel and the weather channel to generate altitude estimation data based upon a target amplitude ratio between the low beam channel and the high beam channel and target range; and

transforming the radar return comprising performing target classification by calculating polarimetric parameters from the target data and the weather data including differential reflectivity and differential phase data, wherein the target channel has a different polarization than the weather channel.

15. The article according to claim 14, wherein the altitude estimation is obtained and improved altitude accuracy is obtained by smoothing over multiple scans.

16. The article according to claim 14, wherein the differential reflectivity and the differential phase are obtained from co-polarization data and reverse polarization data.

17. The article according to claim 16, further including instructions for generating probability values for a target.

18. The article according to claim 17, wherein the probability values correspond to at least birds and aircraft.

19. The article according to claim 14, wherein the differential reflectivity is defined as:

$Z_{\mathrm{DR}}=10·<br><br>{\log }_{10}\left(\frac{I_c^2+Q_c^2}{I_r^2+Q_r^2}\right),$

and the differential phase is defined as;

${\mathrm{\phi <br><br>}}_{\mathrm{DR}}={\tan }^{-1}<br><br>\left(\frac{I_c}{Q_c}\right)-{\tan }^{-1}<br><br>\left(\frac{I_r}{Q_r}\right),$

where R is range, I_c and Q_c are the in-phase and quadrature data of the co-polarization channel, and I_r and Q_r are the in-phase and quadrature data of the reverse polarization channel.