Spatial-Domain Anti-Jamming for Unmanned Systems with Lacking Prior Information

PAN Zihao; ZHANG Bangning; ZHEN Pan; ZHU Bowen; WANG Ning; GUO Daoxing

doi:10.11999/JEIT260296

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PAN Zihao, ZHANG Bangning, ZHEN Pan, ZHU Bowen, WANG Ning, GUO Daoxing. Spatial-Domain Anti-Jamming for Unmanned Systems with Lacking Prior Information[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT260296

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PAN Zihao, ZHANG Bangning, ZHEN Pan, ZHU Bowen, WANG Ning, GUO Daoxing. Spatial-Domain Anti-Jamming for Unmanned Systems with Lacking Prior Information[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT260296

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Spatial-Domain Anti-Jamming for Unmanned Systems with Lacking Prior Information

doi: 10.11999/JEIT260296 cstr: 32379.14.JEIT260296

College of Communications Engineering, Army Engineering University of PLA, Nanjing 210007, China

Accepted Date: 2026-06-29
Rev Recd Date: 2026-06-29

Available Online: 2026-07-13

Abstract

Abstract

Objective Unmanned systems play an increasingly vital role in critical scenarios such as modern emergency response, public safety, intelligent transportation, and so on. Their autonomous perception, intelligent decision-making, and collaborative control capabilities form the core guarantee for efficient task execution. Ensuring the safe, reliable, and continuous operation of unmanned platforms within complex environments constitutes the fundamental basis of unmanned intelligent technology. However, the communication links of unmanned systems are highly susceptible to exposure within open, non-cooperative electromagnetic environments, facing threats of intentional jamming or unintentional interference. Furthermore, communication processes may lack the information of the desired signal, jamming, as well as the multipath effect. This renders existing spatial-domain anti-jamming solutions ineffective, severely compromising the stability of perception, decision-making, and control feedback loops. Consequently, this paper proposes a spatial-domain anti-jamming framework designed to autonomously identify interference, preserve signals, and reconstruct communication links operating in the absence of prior information. Methods The proposed spatial-domain anti-jamming method first employs a spatial smoothing algorithm for the received signal, followed by Capon spatial estimation to detect the direction of arrival (DOA) of incoming signals, where the spatial smoothing aims to decohere for the detection of the DOA for potential multipath signals. Subsequently, spectrum peaks are extracted based on the estimated Capon spatial spectrum, with each peak corresponding to an incident signal. To separate the mixed signals, all estimated peaks are traversed, and a covariance matrix reconstruction-based beamforming algorithm is employed to extract the signals associated with each peak, thereby achieving signal separation. Then, a signal-type identification method based on spectral similarity and time delay is proposed. The KL divergence is used to assess the similarity between each separated signal spectrum and the reference spectrum, with a threshold set to identify jamming. Subsequently, time delay is employed to distinguish direct-path and multipath signals among the remaining signals. Finally, different processing strategies are performed according to the identified signal type. Specifically, multipath signals may be treated as jamming to be suppressed or alternatively combined with a direct-path signal after time-delay alignment. Results and Discussions By designing two cases, including jamming alone and jamming plus multipath, the performance of the proposed method is evaluated using metrics such as output signal-to-jamming-plus-noise ratio (SJNR), beam response, bit error rate (BER), and error vector magnitude (EVM). Simulation results demonstrate that the proposed method consistently maintains near-optimal SINR, which varies with SNR at a fixed SNR (Fig. 3a) and varies with JSR at a fixed SNR (Fig. 3b) under jamming. The time-domain waveform and frequency spectrum after the proposed method remain clearly discernible and consistent with the original signal (Fig. 4). The BER curve nearly overlaps with that of its after optimal processing (Fig. 5). Under $ {E}_{b}/{N}_{0}=10dB $, the constellation diagram is clearly restored, achieving an EVM of -11.52 dB (Fig. 6). Under coexisting jamming and multipath conditions, the proposed method can flexibly handle multipath. Compared to suppression strategies, multipath utilization improves both the output SINR and BER (Fig. 7a and 7b). Beam patterns reveal that a lower secondary lobe forms in the multipath direction after multipath utilization (Fig. 7c). Conclusions This paper proposes a spatial-domain anti-jamming framework for unmanned systems with lacking prior information. Only using the received mixed data, the proposed framework separates signals from different directions and identifies their types. Suppression or retention strategies are then applied based on these types. We finally achieve flexible handling of multipath signals while preserving the direct-path signal and suppressing jamming. Simulation results evaluated the performance of the proposed method in terms of output power and demodulation accuracy, demonstrating its ability to achieve effective jamming suppression and reliable information transmission even under limited prior knowledge regarding jamming, direct-path signal, and multipath characteristics. Future work will analyze the impact of array perturbations, more smart jamming, and coexisting communication modes on the proposal and extend it to increasingly complex unmanned system environments.
- Unmanned Systems,
- Spatial-Domain Anti-Jamming,
- Adaptive Beamforming,
- Spatial Smoothing

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References(37)

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