The conventional frequency diversity array (FDA) can generate arcsine form of continuous direction modulation (DM) waveforms which can automatically scan the entire space range. However, the single waveform and time varying phase of FDA cannot meet the requirements of practical security communication application scenarios. Thus, a new transmit diversity technique, called time frequency direction modulation (TFDM), is proposed to improve azimuth security. In this paper, unique timefrequency information at a given azimuth was formed by designing the beam steering term and the frequency term of each array element on the basis of the time varying characteristics of the FDA. In a transmit duration , DM can be divided into linear DM (LDM) and nonlinear DM (NDM) according to the beam shape. For LDM, for a specific observation direction, the frequency reaches the set value when the beam energy reaches the maximum value when the beam scans to this direction, but the uniqueness of time frequency information no longer exists in other directions. For NDM, the beam can pass through a given azimuth multiple times and form multiple pairs of time-frequency information, which provides a new idea for realizing multi-directional communication and solving communication rate problems. Finally, the uni-directional and multi-directional communication based on three different safe communication methods: time-direction modulation (TDM), frequency-direction modulation (FDM), and time-frequency-direction modulation (TFDM) are realized and the validity of the proposed method and the corresponding theory are verified by extensive numerical results.INDEX TERMS Frequency diversity array(FDA), frequency modulated (FM), time frequency direction modulation(TFDM), security communication.
For the purpose of simultaneously estimating and locating the linear frequency modulation (LFM) emitter with unknown parameters, an innovative approach, i.e., Fast Direct Position Determination (FDPD), is introduced. The proposed algorithm is based on maximum likelihood estimation (MLE) and spectrum detection. To improve the accuracy and overcome the dramatic complexity of plain maximum likelihood formulation, we further derive the objective function equation of Direct Position Determination (DPD) algorithm and present an enhanced strategy to solve the highly nonlinear optimization problem. By combining the two-step localization method, one-step localization method, and short-time Fourier transform (STFT), our approach realizes jointly estimation of the transmitted signal parameters and emitter localization. Simulation results show that the proposed method is superior compared to the existing DPD, and two-step localization algorithms in terms of localization error and computational complexity, especially for low signal-to-noise ratio (SNR).
Due to the time‐varying phase in frequency diverse arrays (FDAs), traditional phase‐based secure communication (SC) methods cannot be utilized. In this reported work, the automatic scanning property of FDAs (time‐varying property) was rederived. This property allows for the presetting of the beam scanning time towards the desired receiver (Bob). Subsequently, this time‐carrying beam design was applied to Low Earth Orbit (LEO) satellites. A satellite‐to‐ground communication method is proposed based on time intervals, which effectively prevents the interception of information by an undesired receiver (Eve). Simulation results are presented to validate the effectiveness of the proposed method.
In this article, the problem of simultaneously estimating and localizing multiple-input multiple-output (MIMO) radar emitters is considered for a distributed multi-station passive localization system, wherein the transmitted signal is unknown for receiver stations. To achieve highly accurate and robust localization performance, a novel algorithm based on the direct position determination (DPD) algorithm, Karhunen–Loève (KL) transform, and feature matching (FM) is addressed to jointly estimate the emitter position and the unknown signal waveform. First, we further derive the objective function of the DPD method and present an enhanced strategy to exploit as much waveform information as possible without any prior knowledge. By applying KL transform and FM techniques, the proposed method achieves MIMO radar emitter identification and emitter localization. The numerical results show that the proposed algorithm outperforms the existing DPD approaches which ignore the transmitted signals, especially for a low signal-to-noise ratio (SNR).
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