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For the integration detection of near space hypersonic weak targets by high pulse repetition frequency (PRF) radar, a novel method named Multi‐Hypothesis Fuzzy‐Matching Radon transform (MHFM‐RT) is proposed for the near space hypersonic target detection and tracking. For remote hypersonic target detection, to avoid range ambiguity, current radars always use a low PRF mode, which limit the number of pulse accumulations. Using the high PRF mode, the fuzzy folding will appear in the target range measurements when target trajectory crosses range fuzzy intervals. Therefore, there is a contradiction between range ambiguity and energy accumulation. The proposed method is used to match the fuzzy measurements, so as to realise the correct integration in the condition of range ambiguity. Firstly, considering the need of range ambiguity resolution, the mode of staggered PRF is used. Secondly, the first frame measurements are periodically extended for multiple‐fuzzy hypothesis. Finally, the weak target track is accumulated in MHFM‐RT domain, and the signal integration and ambiguity resolution can be realised simultaneously. The proposed method expands the Variable‐Diameter‐Arc‐Helix Radon transform (VDAH‐RT) method to fuzzy folding conditions. Compared with the existing methods, for 7‐scan measurements non‐coherent integration, the detection sensitivity of the proposed method is about 0.5–1 dB higher than that of the IMM hybrid filter algorithm, and about 1 dB higher than that of the RHT‐TBD approach, and it needs less storage space and has higher detection probability. [ABSTRACT FROM AUTHOR]

The transmit waveform with ambiguity function specifications in the range‐Doppler plane has been of great interest in traditional single antenna radar systems in recent years. This paper considers the design of waveform sets with a desired slow‐time ambiguity function for multiple‐input multiple‐output radar. Specifically, it is desirable that the ambiguity function has low sidelobes where clutter occurs, as this reduces the impact of the clutter on target detection. Instead of unimodular waveforms, the authors consider amplitude modulation signals and introduce the bound constraint on signal amplitudes into the optimisation for the consideration of transmitter efficiency. The design problem is formulated as minimising the weighted integrated sidelobes level of the ambiguity function over the range‐Doppler plane under bound constraints. The resulting problem has a highly non‐linear objective function and is constrained by bound constraints and quadratic equality (constant energy) constraints, making it difficult to solve. The authors develop an efficient algorithm based on the sequential quadratic programming technique and non‐linear conjugate gradient method to solve it. Simulation results show that the proposed algorithm is superior to the existing methods. [ABSTRACT FROM AUTHOR]

The non‐stationary clutter phenomenon and the severe range ambiguity make space‐based early warning radar as an intricate model of received ground and sea clutter. The received clutter is severely broadened in Doppler dimension, and the degrees of freedom (DOFs) of the received clutter is severely increased. Because the DOFs of the system is always lower than the theoretical DOFs of the received clutter, the adaptive processing capability of the system is insufficient and the performance of clutter suppression is seriously degraded. A multi‐domain cascaded adaptive processing method is proposed in this study. The proposed method takes full advantage of the digital antenna array to suppress a portion of the clutter energy by introducing the transmit pulse coding domain, and the remaining influential clutter energy is suppressed by introducing the elevation‐dimensional receive channel domain. Finally, the clutter after the two‐dimensional (2D) pre‐processed is suppressed by the 2D adaptive processing in the azimuthal receive beam‐receive Doppler domain. This method pre‐processes the clutter data by extending the processing dimension to meet the freedom requirements of the adaptive signal processing, and the capability of clutter suppression is significantly improved. Simulation examples show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This article presents a direction‐finding method based on phase difference measurement for wide‐ranging applications of electronic intelligence. By including three processing steps of rotating, re‐scaling, and rounding of phase plane, the proposed method is able to obtain the actual phase shift of the longest baseline from the ambiguous phase differences measured from incoming signals with low computational cost. The method's performance is analysed and evaluated in terms of angle of arrival (AOA) estimation accuracy and probability of unambiguity by several interferometers of long baselines designed by multiple antenna elements. Consequently, an optimised array configuration of four antenna elements is taken into account to obtain high AOA estimation accuracy via several productive simulations and intensively validated with device measurement in the practical environment. Regarding the simulation of angle estimation accuracy, the proposed method remarkably outperforms two other existing methods, including second‐order difference array and correlative interferometers. In the experimental measurement, high AOA determination performance is achieved with the transmitter located around 35.5 m far from an antenna array and the small average angle estimation error of 1.86° at the direction of 20°. For various directions from −60° to 60° with the steps of 5°, the results satisfy the actual directions of the transmitter with a standard deviation of less than 0.5°. [ABSTRACT FROM AUTHOR]

This study introduces a new scheme for resolving the ambiguity in a pulse‐Doppler radar. While ambiguity resolution is typically performed before tracking, the proposed approach, Track‐Before‐Resolving, is resolving ambiguity utilising tracking filters. A specific Doppler ambiguity resolution algorithm is provided for demonstrating that the Track‐Before‐Resolving method is useful. In order to resolve the ambiguity, which is equivalent to finding the ambiguity number, this algorithm investigates the maximum probability calculated in the multiple model estimation, each with a tracking filter of a different ambiguity number. Simulation shows that the proposed algorithm performs effectively, even at low SNR. [ABSTRACT FROM AUTHOR]

This study proposes a small sample recognition method for radar waveforms based on data enhancement of ambiguity function generative adversarial networks (AFGAN) to address the issue of low recognition rate and unbalanced class recognition rate. First, the concept of ambiguity function efficient contour lines (AFECL) and AFECL subject resolution constant are proposed in order to effectively extract radar waveform features. Based on this, the AFGAN model is proposed for radar waveform data enhancement. Simulation experiments classified and identified six types of radar waveforms, which verifies the effectiveness of the model. The experimental results show that the overall recognition rate is increased by 18.64%–99.25% and the class recognition unbalance is reduced by 40.67%–1.33% under the condition of small samples. Compared with short‐time Fourier transform (STFT) and Wigner‐Ville distribution (WVD), the proposed AFECL features are more suitable for recognition in small samples, and the AFGAN model performs significantly better than that of the classical data enhancement models GAN and general WGAN‐GP. The signal recognition rate reached 94.28% when the SNR was −8 dB. The effectiveness of the AFGAN data enhancement method is verified using comparative experiments. [ABSTRACT FROM AUTHOR]

With the increasing number of available satellites from multi‐global navigation satellite systems (GNSS) and their applications in complicated environments, an increased number of faults in measurements are inevitable. Fault detection and exclusion (FDE) is an effective way to reject observation faults in order to guarantee the integrity of a GNSS positioning and navigation system. We propose a modified between‐receiver single‐differencing (SD)‐based FDE algorithm for real‐time kinematic (RTK) positioning. First, a modified between‐receiver SD model‐based FDE is proposed for testing the estimated float ambiguities. This is helpful in rejecting observations with unreliable float ambiguities and obtaining reliable double‐differencing (DD) integer ambiguities, denoted as the SD float model in the sequel. Second, DD ambiguities are resolved by the DD model and used to update the previous SD float ambiguity. After that, a modified SD fix model, taking the DD ambiguities as the known parameters, is further developed to detect any unreliable or fault‐resolved ambiguities. To verify the modified SD model‐based FDE algorithm, a kinematic vehicle test is conducted. The fault detection test statistics of the SD float model and the SD fix model, time‐to‐first‐fix, ambiguity‐fix rate, SD residuals, and positioning performances are examined. The results show that the modified FDE method can detect and exclude fault satellites accurately and effectively, which is verified by the SD residuals of fault satellites. The ambiguity‐fix rate of the proposed modified FDE algorithm is improved by approximately 3% with 70 more epochs of fixes. Regarding the 3D positioning performance, the modified proposed SD‐based FDE algorithm can achieve 54.11%, 57.78%, and 73.11% improvements for standard deviation, root mean square, and mean bias, respectively, when compared with the processing strategy without the use of the proposed FDE. [ABSTRACT FROM AUTHOR]

In this study, we address the problem of estimating the motion parameters of multiple high‐speed manoeuvering targets under low signal‐to‐noise ratio (SNR) environment with a low‐range resolution radar, where the target movement could cause the echo signal energy seriously spread across both the range and Doppler frequency coordinates, and the returned signals from different targets would merge into each other. Based on the subaperture feature enhancement, Hough transform (HT) and the second‐order short‐time Fourier‐based synchrosqueezing transform (FSST2), a novel method, named as EHFSST2, is proposed. The proposed method can robustly extract the targets of interest from environment and accurately estimate the targets' motion parameters. Thanks to its ability to compensate the effects of the range walk, curvature, and the Doppler ambiguity, spreading, wrapping, and the energy of echo signal can be coherently integrated along the target's individual moving trajectory. In addition, several numerical experiments are provided to demonstrate the effectiveness. The results show that the proposed method is superior to some existing methods in terms of the anti‐noise ability, measurement accuracy and integration performance. [ABSTRACT FROM AUTHOR]

In this study, the authors take further insight into the sparse geometry which offers a larger array aperture than uniform linear array with the same number of physical sensors. A novel direction of arrivals (DOAs) estimation model with flexible sparse geometry, which possesses the potential to significantly improve the estimation performance especially when the placed space and the weight of carrier such as airborne radar are restricted, is proposed to offer a larger aperture compared with co‐prime array. The proposed algorithm can estimate DOAs by solving phase ambiguity. To improve the capability of spectrum analysis in frequency domain, all phase discrete Fourier transform (DFT), which can effectively alleviate spectrum leakage compared with traditional DFT, is proposed to apply into DOAs estimation. Additionally, the performance on degrees of freedom can be considerably improved compared with the state of the art where all the targets can be distinguished by Doppler information of received echo signal. More importantly, the proposed algorithm can effectively deal with DOA‐closely‐spaced targets because the proposed algorithm does not require to estimate signal subspace with ill‐conditioned steering matrices. Both the theoretical analysis and simulation results demonstrate that the proposed algorithm significantly improves DOAs estimation precision with less computation cost. [ABSTRACT FROM AUTHOR]