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In this paper, a new method for detecting and estimating the parameters of a binary phase shift keying (BPSK) signal, based on a cross-correlation function, is proposed. The proposed method consists of two stages. The first stage is used to detect or estimate a signal carrier frequency, and the second stage is used to estimate its pulse width or symbol rate. Firstly, the proposed method is investigated by use of a simulated BPSK signal in the form of Barker Codes 7, 11, and 13 in the MATLAB environment. Based on the simulation results, the functionality of this method is verified using a real-time BPSK signal generated by an E8267C generator. This is described in the second part of this paper. The experimental test results confirm that the proposed method is able to detect and estimate the parameters of all BPSK signals with SNR≥−21 dB.

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In this paper, we propose a new approach to passively locate the 3D position of a signal source. This novel technique, called the power gain difference (PGD), is based only on measuring the received signal strength (RSS) with multiple sensors deployed in the area of interest, while the target transmit power or the equivalent isotropic radiated power (EIRP) is assumed to be unknown. Next, the signal source position is estimated using the knowledge of the ratios of RSS measured on different sensors. First, this article presents the geometric representation and the analytical solution of the model of the PGD technique. Second, the PGD dilution of precision was analyzed in order to gauge the accuracy of measuring the RSS. Finally, a numerical simulation of the performance of the proposed method was carried out and the results are discussed. It seems that the PGD technique has the potential to be a simple and effective solution of the 3D localization problem.

The main aim of this review is to describe in detail an advanced technique to detect and estimate the prior unknown parameters of intra-pulse modulated signals and the verification with typical radar signals. The method is approved for detecting parameters successfully, including chirp rate, carrier frequency, and pulse width. The review presents already-done research on detecting and estimating single and multi-component linear frequency modulation (LFM) and binary phase shift keying (BPSK) signals in a strong noise environment and studies the technique on one more case, a mixture of LFM and BPSK signals. Firstly, the accuracy of the revised technique is shown in detecting and estimating parameters of a single and multi-component LFM signal in white noise and a mixture of continuous wave signals and noise, or a single BPSK signal in strong white noise. All of them have been done in the existing studies. This method is continuously tested in the second part by detecting a mixture of LFM and BPSK signals and estimating their parameters in intense noise. The tested experimental results demonstrate that the technique can detect single and multi-component real-time LFM signals, single BPSK as well as verification with a mixture of real-time LFM and BPSK signals with $$SNR \ge - 12{\text{ dB}}$$ S N R ≥ - 12 dB is performed. As a result, the technique outperforms the existing detection methods based on machine learning and artificial intelligence.

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