Target Echo Signal Research Articles

Radar main‐lobe jamming suppression and identification based on robust whitening Blind Source Separation and Convolutional Neural Networks

The main-lobe jamming causes serious degradation of radar system performance in practical applications. In recent years, the Blind Source Separation (BSS) method has been applied to suppress the main-lobe jamming. However, the received echoes of target and jamming cannot be effectively identified while the robustness of the conventional BSS method is poor due to the influence of system noise. To tackle these problems, a radar main-lobe jamming suppression and identification method is proposed based on robust whitening BSS and Convolutional Neural Networks methods. First, the target echoes and jamming are separated by the proposed robust whitening BSS method. An iterative optimisation method is proposed to obtain the robust whitening matrix, and sufficient conditions are provided for solvability. Then, a Target echo and Jamming Identification Network (TJINet) is proposed to identify the signals after the robust whitening BSS. The proposed TJINet method uses residual blocks and branch structures to improve classification performance and utilises asymmetric convolution blocks to extract subtle features between the target echo and deceptive jamming. Simulation and experimental results show that the proposed method has better jamming suppression performance than the traditional methods under low signal-to-noise ratio (SNR) conditions, the algorithm converges faster, and also can stably identify the target echo and jamming signals.

An Anti-Jamming Method against Two-Dimensional Deception Jamming by Spatial Location Feature Recognition

Interrupted sampling repeater jamming (ISRJ) is an effective method for implementing deception jamming on chirp radars. By means of frequency-shifting jamming processing of the target echo signal and pulse compression during image processing, a group of false targets will appear in different spatial locations around the true target. Extracting the features of these false targets is complex and limited to existing countering methods against ISRJ. This paper proposes an anti-jamming method to identify the spatial location characteristics of two-dimensional deception false targets. By adjusting the parameters of the radar transmitted signal, the method simultaneously transmits the anti-jamming signal and carries out false target identification and elimination in the range and azimuth dimensions. Eventually, the optimal signal parameter design of the anti-jamming signal is obtained by comparing different anti-jamming strategies in the range dimension. The validity of the proposed method is proved by deducing the mathematical model between the spatial distribution characteristics of the false targets and the radar transmitted signal parameters and demonstrated by simulations.

A Method Against Interrupted Sampling Repeater Jamming Based on Genetic Algorithm and Compressed Sensing Reconstruction

By analyzing the discontinuous character in time domain, a jamming suppression method is propose to counter Interrupted sampling reperter jamming(ISRJ, which is an effective coherent jamming to wide-band linear frequency modulation signal. The discontinuous character of ISRJ and the instantaneous frequency change rule after stretch is firstly analyzed. Secondly, by controlling the adjustment parameters, the generalized S transform is utilized to obtain the time-frequency grayscale image of received signal. Then, the grayscale image can be segmented by using genetic algorithm to construct a time-domain filter, and the time-domain filter can be used to extract the echo band without jamming signal. Finally, the extracted signal is used as compressed data to construct a compressed sensing minimization model, and the compressed sampling matching pursuit algorithm is used to reconstruct the target echo signal. Simulation shows that this method has good jamming suppression performance.

The influence analysis of Active Distributed Jamming on radar detection probability

In this paper, we studied the influence of active distributed suppression jamming on radar detection probability. Firstly, the radar detection probability models of three kinds of target echo signals, namely, deterministic signal, Swerlling type I and II signal, Swerlling type III and IV signal, are established under the condition of active distribution; Then, the influence of distributed jamming on the detection probability of three kinds of target echo signals is simulated and analyzed in two kinds of scenarios of distributed support jamming and long-distance distributed support jamming. The simulation results show that the noise power entering the main lobe has the greatest influence on the radar detection probability, but when the noise power in the main lobe increases to a certain extent, the influence on the radar detection probability is not obvious.

Azimuth Resolution Improvement and Target Parameters Inversion for Distributed Shipborne High Frequency Hybrid Sky-Surface Wave Radar

In this paper, the aperture synthesis processing techniques for the distributed shipborne high frequency hybrid sky-surface wave radar (HFHSSWR) are proposed to improve the azimuth resolution and obtain the velocity vector and the azimuth estimation of the moving target. First, the system geometry and the signal model of the moving target for the distributed shipborne HFHSSWR are formulated, and then the azimuth resolution improvement principle is derived. Second, based on the developed signal model, we propose an azimuth resolution improvement algorithm, which can obtain the synthetic azimuth bandwidth and an improved resolution using sub-band combination. Finally, a target parameters inversion method is introduced to estimate the target velocity vector and the target azimuth, by solving the equations regarding the target geometry and echo signal parameters numerically. The simulations are performed to verify the proposed algorithms. The results indicate that the distributed synthetic aperture techniques effectively improve the azimuth resolution of this radar, and can obtain the target velocity vector and the high-precision estimation of the target azimuth.

Analytical Model and Real-Time Calculation of Target Echo Signals on Wideband LFM Radar

In wideband radar system testing and performance evaluation, target echo simulation should simultaneously meet real-time and high-precision requirements. In this paper, we focus on the wideband linear frequency modulated (LFM) radar signal, derive the echo signal time-domain analytical expression based on the multiscattering center model and propose a high-precision real-time echo simulation calculation method. Regarding the low model reliability and poor versatility problems in the current wideband radar target calculation, the analytical model proposed here truly reflects the inner-pulse modulation characteristics of the radar transmit signal and the wideband electromagnetic scattering characteristics of the target. Current wideband radar target signal calculation accuracy and real-time performance are also difficult to balance. Considering this problem, the wideband radar target echo analytical model proposed in this paper avoids the large amount of calculations required for the full numerical calculation and effectively improves the calculation accuracy and real-time performance of wideband radar target echo signal calculations without reducing calculation accuracy. The real-time calculation method involves elaborate amplitude-phase control. Simulation analysis and experimental verification confirmed the reliability and validity of these results. These research results have important theoretical significance and practical application value in the field of hardware-in-the-loop simulation.

Fast ISAR imaging method for complex manoeuvring target based on local polynomial transform‐fast chirp Fourier transform

In ISAR imaging, echo signals of complex manoeuvring targets have to be modelled as multi-component cubic phase signals (m-CPS). In this condition, the Doppler diffusion will seriously affect the quality of ISAR imaging. Herein, a complex manoeuvring target imaging method based on local polynomial transform-fast chirp Fourier transform (LPT-FCFT) is proposed. In this method, the instantaneous frequency and the quadratic chirp rate of the echo signal are estimated by local polynomial transformation, then the chirp rate and the amplitude are estimated by fast chirp Fourier transform, and finally the high-resolution ISAR image of the complex manoeuvring target is obtained by CLEAN technology. Compared with the traditional method, the proposed method has the advantages of less computational complexity, clearer imaging results and better anti-noise performance. Simulation results indicate the effectiveness and superiority of the proposed method.

Target Detection Method Using Heterodyne Single-Photon Radar at Terahertz Frequencies

Different from conventional radar systems, for the single-photon radar, a single-photon detector acts as the receiver to detect the echo signal with only a few photons, which can be used to achieve ultrahigh sensitivity for long-distance target detection. In this letter, the heterodyne single-photon radar at terahertz frequencies is studied, for the first time. First, the working principle of the developed heterodyne single-photon radar is presented, and the target echo signal is derived. Subsequently, the estimation method of the target distance and the Doppler frequency is proposed, and the performance is analyzed by probability density function (PDF) derivation. Simulation results show good agreement with the theoretical analysis. This work can pave the way to the development of a new radar paradigm.

Research on radar main lobe false target jamming feature extraction based on time-frequency domain and fluctuation characteristics

Aiming at radar main lobe false target jamming, the forms of target echo and jamming signal are analyzed, and its modeling and simulation are carried out. By extracting the 11 dimensional features of time domain, frequency domain and amplitude fluctuation characteristics, it is proved that it is distinguishable for real target echo and false target jamming signal through simulation experiment, and a feature model is established; aiming at the shortcomings of traditional classification model, bagging algorithm is applied to deal with the over fitting phenomenon. Simulation results show that the feature model established in this paper has good performance in bagging algorithm.

SNR Enhancement of Back Scattering Signals for Bistatic Radar Based on BeiDou GEO Satellites

Using scattering signals of the global navigation satellite system (GNSS) for target detection has become one of the research hotspots. This technology faces the difficulty of low signal-to-noise ratio (SNR) target echoes. Since BeiDou geostationary orbit (GEO) satellites provide the opportunity to form a bistatic radar with some advantages, such as fixed coverage area and quasi monostatic configuration to avoid the interference from the direct signals, the target echoes may have regular phases that are beneficial to SNR enhancement. This study uses BeiDou GEO satellites and ground fixed receivers to form a bistatic radar and analyzes the phase changes in the reflected signal caused by the target, then gives two methods for SNR enhancement corresponding to two applications: deformation monitoring and ship detection. This paper first introduces the basic signal processing including the intermediate frequency (IF) signal collector and the range compression in the software receiver, then describes the basic SNR enhancement method, i.e., increasing coherence integration time (CIT), and shows its limitation by two target cases: static metal reflector on the land and ships in the water. After that, this study provides an improved SNR enhancement method based on Doppler and range compensation in the moving ship detection case. The experiment shows that by the SNR enhancement, the SNRs of target echo signals in range/Doppler domain increase more than 4 dB on average. This study also demonstrates the bistatic radar’s potential for monitoring surface deformation.

Research on Frequency Estimation Method of Underwater Target Echo Signal for Acoustic Decoy

The body target effect of the torpedo can affect the Doppler frequency estimation accuracy of the torpedo echo signal received by the detonating acoustic decoy fuze, which will cause errors in the position of the detonation point. A joint frequency estimation method of amplitude ratio and segmented phase difference (Rife-Segmented Phase Difference Method, referred to as RP method) is proposed. This method combines the traditional Rife algorithm and the segmented phase difference algorithm. By preprocessing the estimated signal frequency and adopting different estimation algorithms in different frequency bands, and high-precision estimation of Doppler frequency of the target echo signal is achieved. The simulation results show that the method has high estimation accuracy and good stability. It improves the accuracy of extracting the Doppler frequency information of the torpedo target echo, so as to realize the accurate prediction of the tipping point position and improve the probability and effect of torpedo damage. This method can be used for reference by relevant technicians.

Two-Stage Fast DOA Estimation Based on Directional Antennas in Conformal Uniform Circular Array.

In conformal array radar, due to the directivity of antennas, the responses of the echo signals between different antennas are distinct, and some antennas cannot even receive the target echo signal. These phenomena significantly affect the accuracy of direction-of-arrival (DOA) estimation. To implement accurate DOA estimation in a conformal uniform circular array (UCA) composed of directional antennas, the two-stage fast DOA estimation algorithm is proposed. In the pre-processing stage, multi-target decoupling and target detection are mainly used to obtain the targets’ range bin indexes set; in the rough-precise DOA estimation stage, the amplitude and phase information of each antenna are used for rough DOA estimation and precise DOA estimation, respectively. Based on simulation and actual anechoic chamber radar experiments, and through quantitative analyses of the accuracy, validity and elapsed time of the two-stage fast DOA estimation algorithm compared with the directional antenna MUSIC (DA-MUSIC), sub-array MUSIC (S-MUSIC) and Capon-like algorithms, results indicate that the two-stage fast DOA estimation algorithm can rapidly and accurately estimate DOAs in a multi-target scenario without the range-angle pair-matching procedure. Lower computational complexity and superior estimation accuracy provide the two-stage fast DOA estimation algorithm a broader application prospect in the practical engineering field.

Using DTMB‐Based Passive Radar for Small Unmanned Aerial Vehicle Detection

There is inevitable polarization angle deviation between the target echo signal and the direct path signal of illuminator of opportunity (IO) in passive radar. In order to investigate the potential performance loss in target detection induced by the random deviation, small unmanned aerial vehicle (UAV) detection experiments with digital television terrestrial multimedia broadcasting‐ (DTMB‐) based passive radar are conducted in this paper. Experimental results show that the polarization angles of the clutter signal and target echo signal are inconsistent. When the polarization diversity technology is used to suppress the clutter signal, the processing performance of the target echo signal may be reduced. On the premise that clutter is effectively suppressed by the processing algorithm, polarization synthesis can maximize the target echo signal processing gain. The effectiveness of the target localization algorithm combining time difference of arrival (TDOA) and direction of arrival (DOA) is also verified with polarization diversity reception in this paper.

Method of Detecting a Target Enveloped by a Plasma Sheath Based on Doppler Frequency Compensation

The high velocity of the re-entry object causes its surface to be enveloped with a plasma sheath. In the process of target detection of re-entry objects, the plasma sheath with fluid characteristics results in multiple reflected signals in the radar echo. Multiple targets appear in the 1-D range profile following pulse compression processing of a multicomponent echo signal. We refer to targets different from the real target as interference targets. The appearance of interference targets seriously affects the radar detection of re-entry objects, resulting in positioning failure or even tracking loss. In this article, by establishing the physical model of radar echo with multiple reference points and multiple velocity parameters of the re-entry object under plasma sheath, the multitarget phenomenon of the re-entry target echo signal on the 1-D range profile is simulated. A target detection method based on Doppler frequency compensation and nonuniform plasma sheath reflection model is proposed, which can effectively suppress false targets and realize reliable detection of targets under plasma sheath. The feasibility of detecting a target enveloped by a plasma sheath is verified by simulation, laying the foundation for the precise detection and tracking of targets.

Імітатор повітряно-завадової обстановки з використанням системи “Віраж-РД” для оглядових аналогових радіолокаційних станцій

Для якісного навчання бойових обслуг радіолокаційних станцій радіотехнічних військ доцільно використовувати імітатори повітряно-завадової обстановки, яка була б максимально наближена до реальної. Запропоновано імітатор, модель нальоту в якому програмується в персональних електронно-обчислювальних машинах, а відображення обстановки здійснюється на штатних індикаторах кругового огляду радіолокаційних станцій. Для їх зв’язку з комп’ютером розроблені пристрої спряження, які здійснюють синхронізацію роботи та перетворення цифрової інформації у аналогову з подальшою передачею її на радіолокаційну станцію. Для створення повітряно-завадової обстановки використовується система оперативно-тактичних розрахунків та імітаційного моделювання бойових дій “Віраж-РД”. Пристрій спряження виконаний з використанням COTS-технологій на базі сімейства плат Arduino, що дає змогу зробити імітатор низьковартісним. Розроблений імітатор доцільно використовувати в якості тренажно-імітаційного комплексу при навчанні бойових обслуг радіолокаційних станцій.

Echo signal simulation system

In order to meet the demand of realistic simulation for complex target echo signal in water, the indirect method of frequency domain is employed to simulate the target echo signal in this paper. The plate element method is first used to forecast complex target echo characteristics in typical water. After generating frequency response function data, the data is imported into the echo signal simulation system. The system adopts FPGA real-time signal processing system based on PXIe bus. It receives hydrophone output signal by A/D sampling, extracts the incident acoustic signal and makes frequency domain transformation. After multiplying the transformed signal and frequency response function, scattering echo spectrum is obtained. And then the time domain transformation is made to get the time series of the echo signal. The series is loaded into the transmitting transducer by the power amplifier and the echo signal is simulated. The system has the high fidelity of the model, stable and reliable hardware system, and software system for easy operation.

A recognition algorithm of VGPO jamming based on discrete chirp-Fourier transform

This paper addresses the recognition problem of velocity gate pull-off (VGPO) jamming from the target echo signal for the velocity-based tracking system. The discrete chirp-Fourier transform (DCFT) is studied in this paper to jointly estimate the chirp rates and frequencies of the target and jamming signals. Firstly, the scaling characteristic of the DCFT algorithm is explored. Then, we focus on the quantitative effect of the VGPO jamming signal by analyzing the jointly estimated results in each pulse. The quantitative effect indicates that, as long as the estimated frequency is unchanged, the relationship between the estimated chirp rate and the pulse numbers is similar to the relationship between the frequency offset of VGPO jamming and the time. Finally, by utilizing the joint estimated results in each pulse repetition interval and calculating the mean square to variance ratio (MSVR) of the normalized estimated chirp rate, the VGPO jamming can be recognized. Simulation results show that the jamming signal and the target echo become distinguishable with the proposed feature. Comparing to the existing works, the proposed method can correctly recognize the jamming signal with lower jamming-to-noise ratio (JNR) 5 dB with less data needed, which means it can work effectively in the early stage of interference implementation and shows great potential in practical applications.

An Interference Suppression Method for Multistatic Radar Based on Noise Subspace Projection

The mainlobe jamming suppression technique is one of the key techniques of radar electronic counter-countermeasure (ECCM). In the view of multistatic radar, the interference signals received with different view angles would be highly coherent, on the contrary, the target echoes would be independent due to the radar cross section (RCS) of target would randomly fluctuate as the variation of view angle. As a consequence, After the interference signals have been aligned, a steering vector can be found of interference signals, the energy of the interference signals will be concentrated in a single-rank subspace whereas the energy of the target echo signals will be scattered throughout the whole signal space of the multistatic radar. By exploiting this phenomenon, a new mainlobe interference suppression method for multistatic radar is proposed. In this method, the projection matrix is trained based on the time domain sampling data. The interference signals received by multiple node radars with different view angles can be effectively suppressed through the noise subspace projection operation. Then, a general likelihood ratio test detector used for the residual signals after projection operation is derived. The results of simulations indicate that the proposed method can effectively suppress various kinds of mainlobe jamming and improve the detection performance. Furthermore, this method is adaptive to the variation of the interference pattern and the geometric configuration of the node array.

Numerical simulation of backscattered echo signal of lidar in near field of water

In the near-field underwater detection of lidar, the low accuracy of time integration model leads to a lot of noise and a low signal to backscatter ratio during target signal extraction. Aiming at this problem, this paper divides the water into thickness units according to the scale time of the AD acquisition card, and establishes a near-field water echo model of lidar called distance layer summation model(DLSM). According to the underwater optical transmission theory, this paper establishes the formula for the time delay of the echo signal of the water with the system angle. The pulse width error of the calculated and measured results is 0.55ns. The experimental results after normalization show that compared with the time integration model, the pulse width percentage error of the model in this paper is reduced by 18.7 %, the root mean square error is reduced by 0.04, and the signal to backscatter ratio is increased by 8.74 dB. The simulation results of the model in this paper are more consistent with the measured water waveform, which can lay the foundation for the subsequent work of water backscatter suppression and target echo signal extraction.

Deep Learning Method on Target Echo Signal Recognition for Obscurant Penetrating Lidar Detection in Degraded Visual Environments.

With the rapid development of autonomous vehicles and mobile robotics, the desire to advance robust light detection and ranging (Lidar) detection methods for real world applications is increasing. However, this task still suffers in degraded visual environments (DVE), including smoke, dust, fog, and rain, as the aerosols lead to false alarm and dysfunction. Therefore, a novel Lidar target echo signal recognition method, based on a multi-distance measurement and deep learning algorithm is presented in this paper; neither the backscatter suppression nor the denoise functions are required. The 2-D spectrogram images are constructed by using the frequency-distance relation derived from the 1-D echo signals of the Lidar sensor individual cell in the course of approaching target. The characteristics of the target echo signal and noise in the spectrogram images are analyzed and determined; thus, the target recognition criterion is established accordingly. A customized deep learning algorithm is subsequently developed to perform the recognition. The simulation and experimental results demonstrate that the proposed method can significantly improve the Lidar detection performance in DVE.