This paper addresses the problem of direction-of-arrival (DOA) estimation for cyclostationary signals using less reception channel in comparison with the number of sensors. The system is considered to be realized by using the reception channel(s) to receive the signal reached each sensor in turn. Such simplification results in a cost reduction of the system and the effect of inconsistency among different channels are removed. However, non-synchronized sampling also makes the traditional DOA estimation algorithms ineffective. To cope with the problem, the signal models for DOA estimation using a single channel and dual channels are formulated based on signal cyclostationary, and the single channel cyclic MUSIC (SC-Cyclic-MUSIC) algorithm and the dual channels cyclic MUSIC (DC-Cyclic-MUSIC) algorithm are proposed correspondingly. This paper shows that both SC-Cyclic-MUSIC algorithm and DC-Cyclic-MUSIC algorithm work well when the switching interval is known, and a satisfied performance can also be obtained by DC-Cyclic-MUSIC algorithm when the uncertainty of the switching interval exists. Moreover, the proposed estimators are suitable for both narrow-band and wide-band signals. The computer simulations are provided to verify the effectiveness of the proposed algorithms.

This letter addresses the problem of direction-of-arrival (DOA) estimation for cyclostationary signal when the second order cyclic statistics (SOCS) of signals are correlated. We first present a Toeplitz Cyclic-MUSIC algorithm for multi-channels receiver by exploiting signal cyclostationarity. Based on cyclic autocorrelation of the received signal, a new pesudo cyclic covriance matrix which is Toeplitz is constructed. The rank of Toeplitz matrix is equal to the number of signals even if the second order cyclic statistics of signals are correlated. So the MUSIC algorithm can be used to estimate the DOAs of sources. Moreover, a single channel Toeplitz Cyclic-MUSIC algorithm for the single channel receiver is proposed to avoided the affect of channel inconsistency. The effectiveness of the proposed algorithms is verified by computer simulation and the performance of the proposed algorithms is compared with the existing algorithms correspondingly.

In this letter, two time-difference-of-arrival (TDOA) estimation algorithms are studied by employing the cyclostationary property of LFM signals. First, the multicycle frequency phase TDOA (MCFP-TDOA) estimation algorithm is developed by using the phase difference of the cyclic auto-correlation function of each cycle frequency, followed by an analysis on the phase ambiguity problem. By taking advantage of multiple cycle frequencies and the linear relationship between each cycle frequency, it was found to have smaller estimation error compared with the traditional cyclic phase difference (CPD) method. Second, based on the characteristics of LFM signals in the cyclic frequency domain, the spectral correlation TDOA (SC-TDOA) estimation algorithm is devised, which has good antinoise ability. The improved performances of the proposed algorithms are demonstrated through detailed theoretical analysis and simulations.

This paper presents a novel joint TOA-AOA-RSS fingerprint localization method aimed at reducing the necessity for collecting extensive fingerprint data for database construction. Initially, The Time-of-Arrival(TOA) is employed for coarse localization to narrow down the fingerprint database. Subsequently, Angle-of-Arrivals(AOAs) and Received Signal Strengths(RSSs) were used as feature parameters to construct the fingerprint database together with the coarse localization coordinates obtained from the TOA. Finally, a matching algorithm is utilized to determine the coordinate of the localization point. Additionally, we introduce an improved self adaptive weighted K nearest neighbor (ISAWKNN) algorithm is proposed based on Hybrid TOA,AOA, and RSS measurements. Simulation results illustrate the proposed algorithm improving the localization accuracy.

In the field of millimeter wave communication, antenna subset modulation (ASM) is widely known as a low-complex physical layer secure technology. However, the randomly selected antenna subset, may produce severe pedestal secondary lobes. In this letter, an enhanced ASM scheme, simulated annealing based orthogonal matching pursuit (SA-OMP), is proposed. In this idea, the transmit array is initially formulated by SA to implement secure transmission, on the basis of which the receive array can be determined by solving an overdetermined problem with OMP. Hence an equivalent pattern with low sidelobes is derived. Simulation results demonstrate the availability of the proposed approach.

This paper addresses the time-difference-of-arrival (TDOA) estimation problem of almost-cyclostationary signals under accelerated scenarios. First, the signal characteristics of fast-moving targets with constant relative acceleration are analyzed, and the generalized almost-cyclostationary (GACS) property of the received signals is systematically derived. It is worth noting that the cyclostationary frequency of the received signals is time-variant, following the variation pattern of a linear frequency-modulated (LFM) signal. Second, leveraging the distinct features in the cyclic frequency domain, an improved cyclic autocorrelation method based on the fractional Fourier transform (FrFT) is developed. This algorithm enables efficient exploitation of the almost-cyclostationary property across multiple cyclostationary frequencies, leading to a significant reduction in estimation errors. Finally, numerical simulations are performed to validate the effectiveness of the proposed method. The simulation results further demonstrate that it achieves superior performance compared with existing algorithms.