Antenna array calibration in wireless communication systems

• US 6,232,918 B1
• Filed: 09/14/1998
• Issued: 05/15/2001
• Est. Priority Date: 01/08/1997
• Status: Expired due to Fees

• Current Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Original Assignee: US Wireless Corp. (Vontier Corp.)
• Inventors: Jayaraman, Sriram, Wax, Mati, Hilsenrath, Oliver
• Primary Examiner(s): Issing, Gregory C.
• Application Number:
  US09/153,093
• Time in Patent Office: 974 Days
• Field of Search: 342/360, 342/378, 342/451, 342/453, 342/465, 342/174, 342/173, 343/703
• US Class Current: 342/360
• CPC Class Codes: G01C 21/26 specially adapted for navigation in a road network
• CPC Class Codes: G01S 1/022 Means for monitoring or calibrating
• CPC Class Codes: G01S 1/026 of associated receivers
• CPC Class Codes: G01S 5/021 Calibration, monitoring or correction G01S5/0252 takes precedence
• CPC Class Codes: G01S 5/0218 Multipath in signal reception
• CPC Class Codes: G01S 5/02521 using a radio-map
• CPC Class Codes: H04L 67/04 specially adapted for terminals or networks with limited capabilities; specially adapted for terminal portability
• CPC Class Codes: H04L 67/51 Discovery or management thereof, e.g. service location protocol [SLP] or web services
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04L 69/329 in the application layer [OSI layer 7]
• CPC Class Codes: H04L 9/40 Network security protocols
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/20 Services signaling; Auxiliary data signalling, i.e. transmitting data via a non-traffic channel
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

A method and apparatus are provided for easily and accurately calibrating an antenna array in a multipath environment. A calibration table containing spatial signature data together with corresponding location data is used to calibrate the antenna array, i.e. to determine the array response in various directions. The calibration table includes a set of calibrated signal covariances R₁, . . . , R_N together with a set of N corresponding geographical locations. From this data, a set of array calibration vectors {a(θ)} is determined, where each vector a(θ) characterizes the complex signal response of the antenna array in the direction θ. Once the array calibration vectors are determined, this information can be used for direction finding, beamforming, and other enhancements to the performance of the communication system.

Claims

1. In a system for wireless transmitter location finding, a method for determining a response of an antenna array, the method comprising:

(a) measuring from the array a set of N spatial signatures associated with a set of N calibrated transmitter locations, wherein the spatial signatures comprise multipath signal information; and

(b) calculating from the spatial signatures and calibrated locations a set of array calibration vectors {a(θ

)}, where each vector a(θ

) characterizes the complex signal response of the antenna array in the direction θ

.

2. The method of claim 1 wherein the set of N spatial signatures comprises a set of N signal covariances.

3. The method of claim 2 wherein calculating the set of array calibration vectors {a(θ

)} comprises selecting a subset of the calibrated locations contained within an angular sector centered around an angle θ

, and estimating from a subset of signal covariances associated with the subset of locations an array calibration vector a(θ

) for the angular sector.

4. The method of claim 3 wherein estimating the array calibration vector comprises selecting a set of dominant eigenvectors from the subset of signal covariances, combining the dominant eigenvectors to form an average eigenvector for the sector.

5. The method of claim 4 wherein combining the dominant eigenvectors comprises stacking the eigenvectors in a matrix and calculating the best rank-1 approximation to the matrix.

6. The method of claim 5 wherein combining the dominant eigenvectors further comprises using the best rank-1 approximation to exclude some outlying eigenvectors from the set of eigenvectors.