Sparse antenna array design methodologies: A review

Fig. 3. Results obtained by different methods in a nonuniformly spaced array with length L = 14.5λ: (a) Synthesized patterns and (b) Corresponding excitations.

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Fig. 4. Results obtained by different methods in a clustered array (N = 128, d = 0.5λ): (a) Synthesized patterns and (b) half of corresponding excitations.

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Table 1. SLLs obtained by different methods for different size square arrays.

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Table 1. SLLs obtained by different methods for different size square arrays.

Initial array setting			Max SLL (dB)
Array size	Filling factor (%)	Turned ON elements	RDT [18]	HSPSO [12]	cGA [15]	M-cGA [15]	IFTDT [18]	MI-FFT [25]
12×12	48	70	−16.5	−16.7	17.9	−19.4	−17.6	−19.2
24×24	44	254	−20.7	−19.0	−22.0	−23.3	−22.8	−23.5
30×30	60	540	−20.1	−	−23.9	−24.6	−24.3	−26.4

Table 2. Results of nonuniformly spaced arrays optimized by representative methods (d_min is the realized minimum element spacing, and P denotes the number of optimized elements).

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Table 2. Results of nonuniformly spaced arrays optimized by representative methods (d_min is the realized minimum element spacing, and P denotes the number of optimized elements).

Methods	SLL (dB)	D (dBi)	d_min (/λ)	P	T (s)
Chebyshev	−30.0	14.190	0.500	30	−
PSO [28]	−30.1	14.127	0.586	20	6.82
MPM [33]	−29.9	14.188	0.767	18	0.08
BCS [39]	−29.3	14.190	0.675	20	0.29
Reweight. L1 [44]	−30.0	14.197	0.050	21	2.85
ACO [45]	−30.0	14.062	0.600	19	4.52

Table 3. Results of clustered array optimized by representative methods (Q is the number of subarrays, and N_min denotes the realized minimum number of elements in each subarray).

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Table 3. Results of clustered array optimized by representative methods (Q is the number of subarrays, and N_min denotes the realized minimum number of elements in each subarray).

Methods	SLL (dB)	FNBW (°)	D (dBi)	Q	N_min	T (s)
Hybrid GA [52]	−35.9	3.4	19.89	15	4	−
Hybrid I-CPM [61]	−36.3	3.4	19.56	15	4	100.42
TV-norm [64]	−36.5	3.0	20.09	17	4	13.24
CS [65]	−36.5	3.0	20.09	17	3	12.90
CS [65]	−40.0	3.4	19.87	25	1	12.22

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. Sparse antenna array design methodologies: A review[J]. Journal of Electronic Science and Technology, 2024, 22(3): 100276

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Paper Information

Category:

Received: Feb. 29, 2024

Accepted: Aug. 6, 2024

Published Online: Oct. 11, 2024

The Author Email:

DOI:10.1016/j.jnlest.2024.100276

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. SLLs obtained by different methods for different size square arrays.

Table 1. SLLs obtained by different methods for different size square arrays.

Table 2. Results of nonuniformly spaced arrays optimized by representative methods (dmin is the realized minimum element spacing, and P denotes the number of optimized elements).

Table 2. Results of nonuniformly spaced arrays optimized by representative methods (dmin is the realized minimum element spacing, and P denotes the number of optimized elements).

Table 3. Results of clustered array optimized by representative methods (Q is the number of subarrays, and Nmin denotes the realized minimum number of elements in each subarray).

Table 3. Results of clustered array optimized by representative methods (Q is the number of subarrays, and Nmin denotes the realized minimum number of elements in each subarray).

Table 2. Results of nonuniformly spaced arrays optimized by representative methods (d_min is the realized minimum element spacing, and P denotes the number of optimized elements).

Table 2. Results of nonuniformly spaced arrays optimized by representative methods (d_min is the realized minimum element spacing, and P denotes the number of optimized elements).

Table 3. Results of clustered array optimized by representative methods (Q is the number of subarrays, and N_min denotes the realized minimum number of elements in each subarray).

Table 3. Results of clustered array optimized by representative methods (Q is the number of subarrays, and N_min denotes the realized minimum number of elements in each subarray).