Weather radar beam-sharpening and de-quantization

• US 8,618,977 B2
• Filed: 03/18/2011
• Issued: 12/31/2013
• Est. Priority Date: 01/05/2011
• Status: Expired due to Fees

• Current Assignee: Honeywell International Inc.
• Original Assignee: Honeywell International Inc.
• Inventors: Bunch, Brian P.
• Primary Examiner(s): Keith, Jack W
• Assistant Examiner(s): BYTHROW, PETER M
• Application Number:
  US13/051,769
• Publication Number:
  US 20120169531A1
• Time in Patent Office: 1,019 Days
• Field of Search: 342/25.R, 342/25.A, 342/25.B, 342/25.C, 342/25.D, 342/25.E, 342/25.F, 342/26.R, 342/26.A, 342/26.B, 342/26.C, 342/26.D
• US Class Current: 342/26.B
• CPC Class Codes: G01S 13/953 mounted on aircraft
• 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

Systems and methods for improving display quality for at range weather data of smaller antenna size radar weather systems. A processor receives a column of quantized reflectivity data associated with an antenna from a radar system. The processor adjusts the column of quantized reflectivity data based on estimated quantized reflectivity data associated with a beam pattern for an antenna that is larger than the antenna associated with the received column of quantized reflectivity data.

Claims

1. A method comprising:

receiving, by a processor, a vertical column of quantized reflectivity data sampled by an antenna; and

adjusting, by the processor, the vertical column of quantized reflectivity data based on estimated raw reflectivity data associated with a beam pattern for an antenna that has a smaller beamwidth than the antenna associated with the received vertical column of quantized reflectivity data, wherein adjusting the vertical column of quantized reflectivity data comprises iteratively modifying the estimated raw reflectively data to reduce a mean-square-error between the estimated raw reflectivity data and the quantized reflectivity data.

2. The method of claim 1, wherein iteratively modifying the estimated raw reflectively data comprises:

a) providing an estimated large antenna reflectivity signal based on a convolution of an estimated optimum raw reflectivity signal with a first beamwidth function associated with the larger antenna, the estimated large antenna raw reflectivity signal being a first value;

b) creating a second value by adding a predefined adjustment value to the estimated large antenna raw reflectivity signal;

c) creating a third value by subtracting a predefined adjustment value from the estimated large antenna raw reflectivity signal;

d) convolving the first through third values with a second beamwidth function associated with the smaller antenna;

e) generating first, second and third quantized estimated reflectivity values by quantizing the results of the convolution of the first through third values into a previously defined number of altitude levels;

f) comparing the first, second and third quantized estimated reflectivity values with the received quantized reflectivity value;

g) determining, based on the comparisons, which of the first, second and third quantized estimated reflectivity values is closest to the received quantized reflectivity value;

h) adjusting the first, second and third values based on the determined results;

i) repeating d)-h) until an optimum result is attained; and

j) storing the closest quantized estimated reflectivity value in a three-dimensional memory.

3. The method of claim 2, wherein comparing comprises calculating a mean square error (MSE) between each of the first, second and third quantized estimated reflectivity values and the received quantized reflectivity value.

4. The method of claim 3, wherein determining comprises determining which of the MSE calculations results in the lowest MSE value.

5. The method of claim 4, wherein the optimum result comprises an MSE result below a predefined level.

6. The method of claim 4, wherein the optimum result comprises a predefined number of repetitions of d)-h).

7. The method of claim 1, wherein adjusting comprises adjusting only on quantized reflectivity data beyond a predefined range.

8. A system comprising:

a radar system configured to produce a vertical column of quantized reflectivity data sampled by an antenna;

a memory comprising a three-dimensional buffer; and

a processor in signal communication with the radar system and the memory, the processor being configured to adjust the vertical column of quantized reflectivity data based on estimated raw reflectivity data associated with a beam pattern for an antenna that has a smaller beamwidth than the antenna associated with the received vertical column of quantized reflectivity data, wherein the processor is configured to adjust the vertical column of quantized reflectivity data by at least iteratively modifying the estimated raw reflectively data to reduce a mean-square-error between the estimated raw reflectivity data and the quantized reflectivity data.

9. The system of claim 8, wherein the processor is configured to iteratively modify the estimated raw reflectivity data by at least:

a) providing an estimated large antenna raw reflectivity signal based on a convolution of an estimated optimum raw reflectivity signal with a first beamwidth function associated with the larger antenna, the estimated large antenna raw reflectivity signal being a first value;

b) creating a second value by adding a predefined adjustment value to the estimated large antenna raw reflectivity signal;

c) creating a third value by subtracting a predefined adjustment value from the estimated large antenna raw reflectivity signal;

d) convolving the first through third values with a second beamwidth function associated with the smaller antenna;

e) generating first, second and third quantized estimated reflectivity values by quantizing the results of the convolution of the first through third values into a previously defined number of altitude levels;

f) comparing the first, second and third quantized estimated reflectivity values with the received quantized reflectivity value;

g) determining, based on the comparisons, which of the first, second and third quantized estimated reflectivity values is closest to the received quantized reflectivity value;

h) adjusting the first, second and third values based on the determined results;

i) repeating d)-h) until an optimum result is attained; and

j) storing the closest quantized estimated reflectivity value in the memory.

10. The system of claim 9, wherein the processor is configured to compare by at least calculating a mean square error (MSE) between each of the first, second and third quantized estimated reflectivity values and the received quantized reflectivity value.

11. The system of claim 10, wherein the processor is configured to determine by at least determining which of the MSE calculations results in the lowest MSE value.

12. The system of claim 11, wherein the optimum result comprises an MSE result below a predefined level.

13. The system of claim 11, wherein the optimum result comprises a predefined number of repetitions of d)-h).

14. The system of claim 8, wherein the processor is configured to adjust by at least adjusting only on quantized reflectivity data beyond a predefined range.

15. A system comprising:

a radar system configured to produce a vertical column of quantized reflectivity data sampled by an antenna; and

a processor in signal communication with the radar system and the memory, wherein the processor is configured to adjust the vertical column of quantized reflectivity data based on estimated reflectivity data associated with a beam pattern for an antenna that is larger than the antenna associated with the received vertical column of quantized reflectivity data, wherein the processor is configured to adjust the vertical column of quantized reflectivity data by at least;

a) providing an estimated large antenna raw reflectivity signal based on a convolution of an estimated optimum raw reflectivity signal with a first beamwidth function associated with the larger antenna, the estimated large antenna raw reflectivity signal being a first value;

b) creating a second value by adding a predefined adjustment value to the estimated large antenna raw reflectivity signal;

c) creating a third value by subtracting a predefined adjustment value from the estimated large antenna raw reflectivity signal;

d) convolving the first through third values with a second beamwidth function associated with the smaller antenna;

e) generating first, second and third quantized estimated reflectivity values by quantizing the results of the convolution of the first through third values into a previously defined number of altitude levels;

f) comparing the first, second and third quantized estimated reflectivity values with the received quantized reflectivity value;

g) determining, based on the comparisons, which of the first, second and third quantized estimated reflectivity values is closest to the received quantized reflectivity value; and

h) adjusting the first, second and third values based on the determined results.

16. The system of claim 15, further comprising a memory, wherein the processor is further configured to:

i) repeat d)-h) until an optimum result is attained; and

j) store the closest quantized estimated reflectivity value in the memory.

17. The system of claim 15, wherein the processor is configured to determine by at least determining which of the MSE calculations results in the lowest MSE value.

18. The system of claim 17, wherein the optimum result comprises an MSE result below a predefined level.

19. The system of claim 16, wherein the optimum result comprises a predefined number of repetitions of d)-h).

20. The system of claim 15, wherein the processor is configured to adjust by at least adjusting only on quantized reflectivity data beyond a predefined range.