Compact Crossed-Dipole (Turnstile) Antenna for Global Navigation Satellite System (GNSS) Applications
Problem Description
Design Challenges
The design and implementation of the crossed-dipole antenna for GNSS applications [1] is very challenging due to the following reasons:
Very high performance requirements in terms of return loss and axial ratio.
Highly compact design for military gear.
Unconventional non-rectangular (egg-shaped) driven and passive elements.
High Performance Requirements
The performance requirements are set to according to the objectives of the 2014/2015 Innovate UK – the Small Business Research Initiative (SBRI) Global Navigation Satellite System (GNSS) Antenna Design Competition.
- An antenna design competition co-funded by the Ministry of Defence (MoD), UK and Innovate UK.
![](http://ec2-35-176-54-107.eu-west-2.compute.amazonaws.com/wp-content/uploads/2022/01/Layout_Chaoyun-300x98-1.jpg)
The high-performance requirements are stated as follows:
- Bandwidth
- 1.1 GHz to 1.7 GHz
- Maximum Return Loss over the Bandwidth
- Smaller than or equal to -14 dB
- Maximum Axial Ratio (AR) over the Bandwidth
- Smaller than or equal to 3 dB
- Size (highly compact design for placement on military gear)
- 64.0 mm × 64.0 mm × 10.6 mm
Winning Antenna Design
Successful antenna design proposed and implemented by BAE Systems Applied Intelligence Ltd., UK and University of Liverpool, UK:
- Bandwidth
- 1.1 GHz to 1.7 GHz
- Maximum Return Loss over the Bandwidth
- -9.44 dB
- Maximum Axial Ratio (AR) over the Bandwidth
- 5.07 dB
- Size (highly compact design for placement on military gear)
- 64.0 mm × 64.0 mm × 10.6 mm
AI-driven Design with SADEA-III
The optimization problem is stated as follows:
- Maximum reflection coefficient (S11) < -14 dB (1.1 GHz to 1.7 GHz)
- Maximum axial ratio (AR) < 3 dB (1.1 GHz to 1.7 GHz)
Search Ranges of the Design Parameters
![](http://ec2-35-176-54-107.eu-west-2.compute.amazonaws.com/wp-content/uploads/2022/05/table_gnss-300x196.png)
Layout of the antenna
![](http://ec2-35-176-54-107.eu-west-2.compute.amazonaws.com/wp-content/uploads/2022/05/layouT_gnss-214x300.png)
Synthesis and Measurement Results
The design obtained by SADEA-III [2] is verified through a physical implementation.
![](http://ec2-35-176-54-107.eu-west-2.compute.amazonaws.com/wp-content/uploads/2022/01/FabricationAntennaThumb-1.jpg)
![](http://ec2-35-176-54-107.eu-west-2.compute.amazonaws.com/wp-content/uploads/2022/01/S_Parameter_Free_Antenna-768x585-1-480x366-1.jpg)
![](http://ec2-35-176-54-107.eu-west-2.compute.amazonaws.com/wp-content/uploads/2022/01/Axial_Ratio_Free_Antenna-768x636-1.jpg)
For this case:
- The synthesized antenna by SADEA-III obtains a maximum return loss of -15.2 dB and a maximum axial ratio of 2.9 dB over the bandwidth in one day.
- The synthesized antenna by SADEA-III outperforms the winning antenna design in terms of return loss and axial ratio.
- The measurement results are in close agreement with the simulation results.
- The size of the fabricated antenna is 64.0 mm × 64.0mm × 10.6 mm, which is compact.
Comparison with Other Methods
The performances of SADEA-III [2] and SADEA-I [3] are compared with the following methods:
- 2019 Computer Simulation Technology-Microwave Studio: Particle Swarm Optimization (2019 CST-MWS: PSO)
- 2019 Computer Simulation Technology-Microwave Studio: Trust Region Framework (2019 CST-MWS: TRF)
- A sigma value of unity is used to direct the search towards global optimum and all initial designs for each run are randomly generated using Latin hypercube sampling.
![](http://ec2-35-176-54-107.eu-west-2.compute.amazonaws.com/wp-content/uploads/2022/01/Table_Egg_Antenna-768x241-1.jpg)
Note that results from designs with geometric constraint violation are not included and are designated as not applicable (N/A) because in practice, such designs cannot be used due to geometric incongruities.
![](http://ec2-35-176-54-107.eu-west-2.compute.amazonaws.com/wp-content/uploads/2022/01/egg_trend-768x209-1.jpg)
References
[1]:
- Y. Huang and C. Song, “A Compact Broadband Circularly Polarized Cross-Dipole Antenna for GNSS Applications.“ UK Patent Application GB 2552828 A, 2016.
[2]:
- B. Liu, M. O. Akinsolu, N. Ali and R. Abd-Alhameed, “Efficient Global Optimisation of Microwave Antennas Based on a Parallel Surrogate Model-Assisted Evolutionary Algorithm“, IET Microwaves, Antennas and Propagation, vol. 13, no. 2, pp. 149 – 155, 2019.
[3]:
- B. Liu, H. Aliakbarian, Z. Ma, G. A. Vandenbosch, G. Gielen and P. Excell, “An Efficient Method for Antenna Design Optimization based on Evolutionary Computation and Machine Learning Techniques.“, IEEE Transactions on Antennas and Propagation, vol. 62, no. 1, pp. 7 – 18, 2014.