Cyclic Switching for Sparse Array Antenna Covariance
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Solution Overview
Problem
Sparse array antennas face ambiguity in calculating the covariance matrix of received signal vectors due to spatial undersampling, which limits their ability to estimate Direction of Arrival (DOA) and other applications like channel estimation and interference suppression.
Innovation Solution
An array antenna arrangement with switches connected to radio chains, cyclically configuring antenna elements to form sub-arrays, allowing for the calculation of an unambiguous total covariance matrix by combining covariance sub-matrices from multiple sets of received signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a sparse array antenna is used to reduce the number of receivers/transmitters, then the number of receivers/transmitters is lowered and mutual coupling is reduced, but the covariance matrix becomes ambiguous due to spatial undersampling
Solution Approach 1:
The antenna array is divided into multiple sub-arrays, each connected to a separate radio chain. By segmenting the array and using switches to cyclically connect different sub-arrays to each radio chain, the system can collect sufficient signal samples from all antenna elements over time, resolving the spatial undersampling issue while maintaining a reduced number of permanent receivers/transmitters
Solution Approach 2:
Switches are used to cyclically connect different antenna sub-arrays to each radio chain in a periodic manner. This periodic switching allows each radio chain to receive signals from multiple different sub-arrays over time, enabling the construction of a complete and unambiguous covariance matrix through time-sequential sampling of all antenna elements
2Object-generated harmful factors
If antenna elements are spaced apart more than λ/2 in a sparse array, then mutual coupling between antenna elements is lowered, but the covariance matrix becomes ambiguous due to spatial undersampling
Solution Approach 1:
The sparse array is segmented into multiple sub-arrays that are cyclically connected to radio chains. This segmentation allows the system to maintain the beneficial large spacing (reducing mutual coupling) while still achieving complete spatial sampling through the cyclic switching of different sub-arrays to each radio chain over time
Solution Approach 2:
Switches act as intermediary devices between the sparsely spaced antenna elements and the radio chains. These switches enable the system to overcome the spatial undersampling problem by dynamically reconfiguring which sub-arrays are connected to which radio chains, thereby mediating between the physical constraint of sparse spacing and the computational requirement for complete covariance matrix calculation
Data Source
AI summary
The present invention relates to an array antenna arrangement comprising at least two antenna sub-arrays and at least one antenna element in each antenna sub-array. The array antenna arrangement is adapted for calculation of a total covariance matrix (R) of a received signal vector (x). The array antenna arrangement further comprises at least one switch, where the number of switches corresponds to the number of antenna elements in each antenna sub-array. Each switch is connected to a respective radio chain, and is arranged to connect the antenna elements of a respective corresponding antenna sub-array to the respective radio chain cyclically. At least one full switch cycle, comprising a set of received signals for each switch configuration, is carried out for a calculation of the total covariance matrix (R). The present invention also relates to a corresponding method.