Chirp sequence has been adopted in automotive applications for its simple generation and flexible integration within radar-centric systems. Besides, recent studies have shown its ability to carry data between communicating vehicles in the surroundings. Since the parameters adopted from current automotive radar sensors can differ at the transmitter side dependent on the automotive supplier, the carrier alignment of the communication receiver of one of the communicated nodes might not concur with the one in the transmitter. This paper presents a novel two-stage synchronization method for communication-assisted chirp sequence (CaCS) signals. The proposed synchronization method applies a sequence of up- and down-chirp as a preamble to estimate frequency and time offsets during the transmission. The suggested synchronization scheme supports partial chirp modulation systems and can be adapted for similar radar-centric systems that employ chirp modulation. The former stage performs a coarse synchronization, reallocates the receive carrier frequency, and corrects eventual time offsets between the communication receiver from one CaCS-node and the transmitter of another node. The carrier allocation at the communication receiver side is based on a combination of spectrum sensing via short-time Fourier transforms and image processing to estimate the transmitting signal pattern (slope, frequency offset, and delay). The latter stage, in its turn, relies on range-Doppler estimation to perform a fine correction of time and frequency offsets and compensates residual offsets of the coarse synchronization stage. Furthermore, the paper analyzes the case of a multi-user scenario with mutual interference between the signals that affects the synchronization and communication data detection. Besides, measurements are provided based on two completely unsynchronized software-defined radios to validate the proposed method. The study also illustrates the influence of the signal-to-noise ratio on the proposed method and verifies it with simulations in MATLAB. As a result, the offsets at the investigated CaCS-node are returned to recover the transmitted data correctly.
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