Multi-Channel Switching Array DOA Estimation Algorithm Based on FRIDA

CHEN Tao; XI Haolin; ZHAN Lei; YU Yuwei

doi:10.11999/JEIT250350

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CHEN Tao, XI Haolin, ZHAN Lei, YU Yuwei. Multi-Channel Switching Array DOA Estimation Algorithm Based on FRIDA[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250350

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CHEN Tao, XI Haolin, ZHAN Lei, YU Yuwei. Multi-Channel Switching Array DOA Estimation Algorithm Based on FRIDA[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250350

CHEN Tao, XI Haolin, ZHAN Lei, YU Yuwei. Multi-Channel Switching Array DOA Estimation Algorithm Based on FRIDA[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250350

Citation:

CHEN Tao, XI Haolin, ZHAN Lei, YU Yuwei. Multi-Channel Switching Array DOA Estimation Algorithm Based on FRIDA[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250350

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Multi-Channel Switching Array DOA Estimation Algorithm Based on FRIDA

doi: 10.11999/JEIT250350 cstr: 32379.14.JEIT250350

CHEN Tao¹,
XI Haolin¹,
ZHAN Lei²,
YU Yuwei^{1
,
,}

1.
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
2.
Chengdu LandTop Technology Co., Ltd, Chengdu 610045, China

Funds: The National Natural Science Foundation of China (62071137)

Received Date: 2025-05-06
Accepted Date: 2025-11-03
Rev Recd Date: 2025-11-03

Available Online: 2025-11-12

Abstract

Abstract

Objective With the increasing complexity of electromagnetic environments, the demand for higher estimation accuracy in practical direction-finding systems is rising. Enlarging the antenna array is an effective approach to improve estimation accuracy; however, it also significantly increases system complexity. This study aims to reduce the number of channels required while preserving the Direction-Of-Arrival (DOA) estimation performance achievable with full-channel data. By combining the channel compression algorithm, which reduces channel usage, with the time-modulated array structure that incorporates RF front-end switches, this paper proposes a multi-channel switching array DOA estimation algorithm based on FRIDA. Methods The algorithm introduces a selection matrix composed of switches between the antenna array and the channels. This matrix directs the signal received by a selected antenna into the corresponding channel, thereby enabling a specific subarray to capture the data. By switching across different subarrays, multiple reduced-channel received data covariance matrices are collected. To ensure phase consistency within these covariance matrices, common array elements are specified for each subarray. After weighted summation, these covariance matrices are combined to restore the dimensionality of the covariance matrix, producing the total covariance matrix. Next, the elements of the total covariance matrix that correspond to identical array-element spacings are weighted and summed, yielding the full-channel received data vector. Using this vector, an FRI reconstruction model is established. Finally, the incident angle is estimated through the combination of the proximal gradient descent algorithm and the parameter recovery algorithm. Results and Discussions Simulation results of DOA estimation for SA-FRI under multiple source incidence demonstrate that the full-channel received data vectors reconstructed from multiple covariance matrices of reduced-channel data can successfully discriminate multi-source incident signals, achieving performance comparable to that of full-channel data (Fig. 2). Further simulations evaluating estimation accuracy with varying numbers of snapshots and Signal-to-Noise Ratios (SNRs) show that the accuracy of the proposed algorithm improves with increasing snapshots and SNR. Under identical conditions, the use of more channels yields higher DOA estimation accuracy (Figs. 3 and 4). Comparisons of four different algorithms under varying SNRs and snapshot numbers indicate that estimation accuracy increases with both parameters. The proposed algorithm consistently outperforms the other algorithms under the same conditions (Figs. 5 and 6). Finally, verification with measured data produces results consistent with the simulations (Fig. 9), further confirming the effectiveness of the proposed algorithm. Conclusions To address the challenge of reducing the number of channels in practical DOA estimation systems, this study proposes an array-switching DOA estimation method based on proximal gradient descent. The algorithm first reduces channel usage through a switching matrix, then generates multiple covariance matrices by sequentially switching different subarray access channels. These covariance matrices are combined to reconstruct the full-channel received data covariance matrix. Finally, the DOA parameters of incident signals are estimated using the proximal gradient descent algorithm. Simulation results confirm that the proposed algorithm achieves reduced channel usage while maintaining reliable estimation accuracy. Moreover, validation with measured data collected from an actual DOA estimation system demonstrates results consistent with the simulations, further verifying the algorithm’s effectiveness.
- Switching array,
- Received data reconstruction,
- Proximal gradient descent,
- Gridless DOA estimation,
- FRI reconstruction model

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References(22)

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