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The Wigner–Ville distribution (WD) and ambiguity function (AF) are serviceable tools for the global analysis of non-stationary signals. However, when dealing with time-varying signals that exhibit changing characteristics and require real-time signal processing, they have high limitations due to the existence of cross-items. In this paper, we propose the short-time Wigner–Ville distribution (STWD) as a novel approach that effectively analyzes time-varying signals with changing characteristics. First, the definition of STWD and short-time ambiguity function (STAF) and their properties are advanced. Next, three uncertainty principles that define the lower bound for the product of signal spread and its bandwidth are derived. Then, the discrete STWD (DSTWD) and the process of computerization are also proposed which can be used more widely in practice. Finally, the optimization of window functions based on Rényi entropy is discussed. Simulation experiments show that the STWD can be effectively applied for the analysis of local change characteristics and real-time processing of signals with valid and accurate results. • The short-time Wigner-Ville distribution (STWD) is proposed. • Three uncertainty principles of the STWD are derived. • Discrete STWD and window function optimization based on Rényi entropy are discussed. [ABSTRACT FROM AUTHOR]

For pulse Doppler radars, targets become undetectable for Doppler frequencies in the detection-blind range occupied by the clutter Doppler spectrum. To overcome this problem, different Pulse Repetition Frequencies (PRFs) are used to search for targets with Doppler ambiguity and estimate their velocity, which is required for target tracking. Owing to the different PRFs used for velocity estimation, many beam dwells are required for illuminating the targets, Doppler compensation cannot be realized in a short time. In this paper, we propose a novel velocity estimation method that uses multicarrier signals in a single dwell. First, we obtain separated subcarrier signals from the echo signal and multiply some separated subcarrier signals by other separated subcarrier signals in a conjugate manner, obtaining Frequency-Converted Subcarrier (FCS) signals. We derive the potential ambiguous and unambiguous Doppler frequencies for the separated subcarrier and FCS signals, respectively, using a slow-time Discrete Fourier Transformation (DFT). Subsequently, the actual Doppler ambiguity number is derived from the results. Finally, the unambiguous Doppler frequency and target velocity are inferred. The effectiveness and superiority of the proposed method are validated by performing simulation studies. • Extending the unambiguous Doppler range. • Simple implementation. • Solving Doppler ambiguity at a PRF. [ABSTRACT FROM AUTHOR]

The coexistence of clutter range ambiguity and range dependence in the airborne forward-looking radar may render the common space–time adaptive processing (STAP) ineffective. To cope with this challenge, a novel vertical element-pulse coding (EPC) radar is proposed in our paper. Note that both the elevation angles and coding factors determine the transmitted spatial frequency of the proposed vertical EPC radar. Therefore, the clutters corresponding to different ambiguous areas can be distinguished in the spatial frequency dimension based on this property. The element-pulse decoding and pre-STAP filtering are devised to separate and extract these clutters corresponding to different ambiguous areas. In the following, the clutter elimination is independently accomplished for each ambiguous area that has been separated. Consequently, the clutter range ambiguity as well as clutter range dependence are addressed simultaneously. The efficacy of the proposed approach is verified with simulation experiments. • A general signal model of vertical EPC array radar is established. • Clutter properties are analyzed in the vertical spatial frequency domain. • Range-ambiguous clutter is separated using element-pulse decoding and pre-filtering. • The design criteria of the element-pulse coding factor are derived. [ABSTRACT FROM AUTHOR]

Range ambiguity is a significant challenge in conventional pulse-Doppler radar systems with medium or high pulse repetition frequencies, greatly impacting radar detection and imaging capabilities. The classic approaches such as waveform diversity and compressed sensing are based on the isolation between pulses. However, these methods encounter issues like residual ambiguity and grid mismatch, resulting in poor range ambiguity suppression performance. In this paper, the multiple signal classification-alternating projection (MUSIC-AP) method is proposed to address these challenges and achieve high-resolution estimation. The proposed method converts the range-velocity estimate into a spectrum estimate, enabling the utilization of the MUSIC algorithm to solve the grid mismatch problem and improve echo reconstruction. Then, to mitigate the effect of ambiguous energy on reconstruction, the MUSIC reconstruction subprocess is embedded into the AP framework. Through iterative approximation, the method gradually suppresses ambiguous and noise energy, thereby further enhancing the echo reconstruction accuracy and range ambiguity suppression performance. Simulations demonstrate the effectiveness of the proposed method. Moreover, algorithm analysis is conducted, considering aspects such as resolution, robustness, and sparsity, which provides a basis for parameter selection and applicability conditions. [Display omitted] • The range-velocity estimation is transformed into spectrum estimation problem. • Unambiguous range-velocity high-resolution estimation via the MUSIC algorithm. • The MUSIC is embedded into AP outer frame to gradually suppress ambiguity and noise. [ABSTRACT FROM AUTHOR]