Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (9)

Search Parameters:
Keywords = moving targets detection (MTI)

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
14 pages, 3599 KB  
Communication
Cascade Clutter Suppression Method for Airborne Frequency Diversity Array Radar Based on Elevation Oblique Subspace Projection and Azimuth-Doppler Space-Time Adaptive Processing
by Rongwei Lu, Yifeng Wu, Lei Zhang and Ziyi Chen
Remote Sens. 2024, 16(17), 3198; https://doi.org/10.3390/rs16173198 - 29 Aug 2024
Viewed by 1294
Abstract
Airborne Frequency Diversity Array (FDA) radar operating at a high pulse repetition frequency encounters severe range-ambiguous clutter. The slight frequency increments introduced by the FDA result in angle and range coupling. Under these conditions, conventional space-time adaptive processing (STAP) often exhibits diminished performance [...] Read more.
Airborne Frequency Diversity Array (FDA) radar operating at a high pulse repetition frequency encounters severe range-ambiguous clutter. The slight frequency increments introduced by the FDA result in angle and range coupling. Under these conditions, conventional space-time adaptive processing (STAP) often exhibits diminished performance or fails, complicating target detection. This paper proposes a method combining elevation oblique subspace projection with azimuth-Doppler STAP to suppress range-ambiguous clutter. The method compensates for the quadratic range dependence by analyzing the relationship between elevation frequency and range. It uses an elevation oblique subspace projection technique to construct an elevation adaptive filter, which separates clutter from ambiguous regions. Finally, residual clutter suppression is achieved through azimuth-Doppler STAP, enhancing target detection performance. Simulation results demonstrate that the proposed method effectively addresses range dependence and ambiguity issues, improving target detection performance in complex airborne FDA radar environments. Full article
(This article belongs to the Section Remote Sensing Perspective)
Show Figures

Figure 1

15 pages, 2459 KB  
Article
Detection and Localization of Small Moving Objects in the Presence of Sensor and Platform Movement
by Adam Cuellar, Abhijit Mahalanobis, C. Kyle Renshaw and Wasfy Mikhael
Sensors 2024, 24(4), 1218; https://doi.org/10.3390/s24041218 - 14 Feb 2024
Cited by 1 | Viewed by 1821
Abstract
In this paper, we address the challenge of detecting small moving targets in dynamic environments characterized by the concurrent movement of both platform and sensor. In such cases, simple image-based frame registration and optical flow analysis cannot be used to detect moving targets. [...] Read more.
In this paper, we address the challenge of detecting small moving targets in dynamic environments characterized by the concurrent movement of both platform and sensor. In such cases, simple image-based frame registration and optical flow analysis cannot be used to detect moving targets. To tackle this, it is necessary to use sensor and platform meta-data in addition to image analysis for temporal and spatial anomaly detection. To this end, we investigate techniques that utilize inertial data to enhance frame-to-frame registration, consistently yielding improved detection outcomes when compared against purely feature-based techniques. For cases where image registration is not possible even with metadata, we propose single-frame spatial anomaly detection and then estimate the range to the target using the platform velocity. The behavior of the estimated range over time helps us to discern targets from clutter. Finally, we show that a KNN classifier can be used to further reduce the false alarm rate without a significant reduction in detection performance. The proposed strategies offer a robust solution for the detection of moving targets in dynamically challenging settings. Full article
(This article belongs to the Section Sensing and Imaging)
Show Figures

Figure 1

17 pages, 2126 KB  
Communication
End-to-End Moving Target Indication for Airborne Radar Using Deep Learning
by Yao Gu, Jianxin Wu, Yuyuan Fang, Lei Zhang and Qiang Zhang
Remote Sens. 2022, 14(21), 5354; https://doi.org/10.3390/rs14215354 - 26 Oct 2022
Cited by 8 | Viewed by 4040
Abstract
Moving target indication (MTI) based on space–time adaptive processing (STAP) has been widely used in airborne radar due to its ability for clutter suppression performance. However, the existing MTI methods suffer from the problems of insufficient training samples and low detection probability in [...] Read more.
Moving target indication (MTI) based on space–time adaptive processing (STAP) has been widely used in airborne radar due to its ability for clutter suppression performance. However, the existing MTI methods suffer from the problems of insufficient training samples and low detection probability in a non-homogeneous clutter environment. To address these issues, this paper proposes a novel deep learning framework to improve target indication capability. First, combined with the problems of target indication caused by the non-homogeneous clutter, the clutter-plus-target training dataset was modeled by simulation, where various non-ideal factors, such as aircraft crabbing, array errors and internal clutter motion (ICM), were considered. The dataset considers various realistic situations, making the proposed method more robust. Then, a five-layer two-dimensional convolutional neural network (D2CNN) was designed and applied to learn the clutter and target characteristics distribution. The proposed D2CNN can predict the target with a high resolution to implement an end-to-end moving target indication (ETE-MTI) with a higher detection accuracy. In this D2CNN, the input was obtained by the clutter-plus-target angle-Doppler spectrum with a low-resolution estimated only by a few samples. The label was given by the target angle-Doppler spectrum with a high-resolution obtained by the target’s exact angle and Doppler. Thirdly, the proposed method used a few samples to improve the target indication and detection probability, which solved the problem of insufficient samples in the non-homogeneous clutter environments. To elaborate, the proposed method directly implements ETE-MTI without the support of the conventional STAP algorithm to suppress the clutter. The results verify the validity and the robustness of the proposed ETE-MTI with a few samples in the non-homogeneous and low signal-to-clutter ratio (SCR) environments. Full article
(This article belongs to the Special Issue Small or Moving Target Detection with Advanced Radar System)
Show Figures

Graphical abstract

24 pages, 10465 KB  
Article
Experimental Study of Maritime Moving Target Detection Using Hitchhiking Bistatic Radar
by Jie Song, Wei Xiong, Xiaolong Chen and Yuan Lu
Remote Sens. 2022, 14(15), 3611; https://doi.org/10.3390/rs14153611 - 28 Jul 2022
Cited by 13 | Viewed by 3656
Abstract
Hitchhiking bistatic radar system takes the direct wave signal that is transmitted by the non-cooperative radar emitter as the reference to detect and analyze the target echo signal, so as to realize the positioning and tracking of the target. This radar system has [...] Read more.
Hitchhiking bistatic radar system takes the direct wave signal that is transmitted by the non-cooperative radar emitter as the reference to detect and analyze the target echo signal, so as to realize the positioning and tracking of the target. This radar system has the advantages of low cost and strong survivability. Aiming at the problem of passive radar to covert the detection of maritime targets, this paper develops a hitchhiking bistatic radar system for maritime target detection, which uses the shore-based radar as the non-cooperative radar emitter. By continuously collecting the direct wave and target echo data of the non-cooperative radar, the direct wave reference signal reconstruction, pulse compression, interference suppression and synchronization processing, non-coherent integration, MTI (moving target indication), clutter map processing, and adaptive CFAR (constant false alarm rate) detection are completed to obtain the azimuth, bistatic range, and Doppler frequency of the target, and finally realize the positioning of non-cooperative maritime targets. This paper first introduces and demonstrates the composition principle of the system, introduces the signal processing implementation method of the system in detail, and tests and analyzes the key algorithms. The experimental results show that the system can realize the passive coherent detection of maritime moving targets and locate multiple targets at the same time. The experiment obtains a very clear PPI (plane position indicator) display picture of the hitchhiking bistatic radar system, and the radar detection data of the experimental system is in good agreement with the AIS (automatic identification system) data. Full article
(This article belongs to the Special Issue Radar High-Speed Target Detection, Tracking, Imaging and Recognition)
Show Figures

Graphical abstract

22 pages, 7297 KB  
Article
A Long-Time Coherent Integration STAP for GEO Spaceborne-Airborne Bistatic SAR
by Chang Cui, Xichao Dong, Zhiyang Chen, Cheng Hu and Weiming Tian
Remote Sens. 2022, 14(3), 593; https://doi.org/10.3390/rs14030593 - 26 Jan 2022
Cited by 12 | Viewed by 3243
Abstract
A geosynchronous spaceborne-airborne bistatic synthetic aperture radar (GEO SA-BSAR) system is an important technique to achieve long-time moving target monitoring over a wide area. However, due to special bistatic configuration of GEO SA-BSAR, two major challenges, i.e., severe range migration and space-variant Doppler [...] Read more.
A geosynchronous spaceborne-airborne bistatic synthetic aperture radar (GEO SA-BSAR) system is an important technique to achieve long-time moving target monitoring over a wide area. However, due to special bistatic configuration of GEO SA-BSAR, two major challenges, i.e., severe range migration and space-variant Doppler parameters for moving targets, hinder the moving target indication (MTI) processing. Traditional SAR MTI methods, which do not take the challenges into consideration, will defocus the moving targets, leading to a loss of the signal-to-noise ratio (SNR). To focus moving targets and estimate motion parameters accurately, long-time coherent integration space-time adaptive processing (LTCI-STAP) is proposed for GEO SA-BSAR MTI in this paper. First, a modified adaptive spatial filtering based on the bistatic signal model is performed to suppress the clutter. Then, an LTCI filter bank is constructed to achieve range migration correction and moving target focusing, which yields the optimal output signal and filtering parameters. Finally, constant false alarm rate (CFAR) detection is carried out to determine the targets, and the space-variant Doppler parameters, solved from the filtering parameters, are used for estimating moving target positions and velocities. Simulations verify the effectiveness of our method. Full article
(This article belongs to the Special Issue Distributed Spaceborne SAR: Systems, Algorithms, and Applications)
Show Figures

Graphical abstract

23 pages, 6365 KB  
Article
Geosynchronous Spaceborne-Airborne Bistatic Moving Target Indication System: Performance Analysis and Configuration Design
by Xichao Dong, Chang Cui, Yuanhao Li and Cheng Hu
Remote Sens. 2020, 12(11), 1810; https://doi.org/10.3390/rs12111810 - 3 Jun 2020
Cited by 20 | Viewed by 3603
Abstract
Geosynchronous spaceborne-airborne bistatic synthetic aperture radar (GEO SA-BSAR), consisting of GEO transmitter and airborne receiver, has stable coverage for a long time and benefits moving target detection. However, the performance of GEO SA-BSAR moving target indication (MTI) system varies widely between bistatic configurations. [...] Read more.
Geosynchronous spaceborne-airborne bistatic synthetic aperture radar (GEO SA-BSAR), consisting of GEO transmitter and airborne receiver, has stable coverage for a long time and benefits moving target detection. However, the performance of GEO SA-BSAR moving target indication (MTI) system varies widely between bistatic configurations. The traditional configuration design for GEO SA-BSAR system only considers the imaging performance, which may cause the poor MTI performance. In this paper, we propose a bistatic configuration design method to jointly optimize the MTI and SAR imaging performance for GEO SA-BSAR MTI system. The relationship between the MTI performance and bistatic configuration parameters is derived analytically and analyzed based on the maximum output signal to clutter and noise ratio (SCNR) criterion. Then, the MTI performance and SAR imaging performance are jointly considered to model the configuration design problem as a multi-objective optimization problem under the constrained condition. Finally, the optimal configuration for GEO SA-BSAR MTI system is given. Full article
Show Figures

Figure 1

18 pages, 10108 KB  
Article
Innovative Multi-Target Estimating with Clutter-Suppression Technique for Pulsed Radar Systems
by Jo-Yen Nieh and Yuan-Pin Cheng
Sensors 2020, 20(9), 2446; https://doi.org/10.3390/s20092446 - 25 Apr 2020
Cited by 6 | Viewed by 4289
Abstract
Linear frequency modulation (LFM) waveforms have high Doppler-shift endurance because of the relative wide modulation bandwidth to the Doppler variation. The Doppler shift of the moving objects, nevertheless, constantly introduces obscure detection range offsets despite the exceptional Doppler tolerance in detection energy loss [...] Read more.
Linear frequency modulation (LFM) waveforms have high Doppler-shift endurance because of the relative wide modulation bandwidth to the Doppler variation. The Doppler shift of the moving objects, nevertheless, constantly introduces obscure detection range offsets despite the exceptional Doppler tolerance in detection energy loss from LFM. An up-down-chirped LFM waveform is an efficient scheme to resolve the true target location and velocity by averaging the detection offset of two detection pairs from each single chirp LFM in opposite slopes. However, in multiple velocity-vary-target scenarios, without an efficient grouping scheme to find the detection pair of each moving target, the ambiguous detection results confine the applicability of precise target estimation by using these Doppler-tolerated waveforms. A succinct, three-multi-Doppler-shift-compensation (MDSC) scheme is applied to resolve the range and velocity of two moving objects by sorting the correct LFM detection pair of each target, even though the unresolvable scenarios of two close-by targets imply a fatal disability of detecting objects under a cluttered background. An innovative clutter-suppressed multi-Doppler-shift compensation (CS-MDSC) scheme is introduced in this research to compensate for the critical insufficient of resolving two overlapping objects with different velocities by solely MDSC. The CS-MDSC has been shown to successfully overcome this ambiguous scenario by integrating Doppler-selective moving target indication (MTI) filters to mitigate the distorting of near-zero-Doppler objects. Full article
Show Figures

Figure 1

17 pages, 2079 KB  
Article
A Low-Complexity FMCW Surveillance Radar Algorithm Using Two Random Beat Signals
by Bong-seok Kim, Youngseok Jin, Sangdong Kim and Jonghun Lee
Sensors 2019, 19(3), 608; https://doi.org/10.3390/s19030608 - 31 Jan 2019
Cited by 21 | Viewed by 7426
Abstract
This paper proposes a low-complexity frequency-modulated continuous wave (FMCW) surveillance radar algorithm using random dual chirps in order to overcome the blind-speed problem and reduce the computational complexity. In surveillance radar algorithm, the most widely used moving target indicator (MTI) algorithm is proposed [...] Read more.
This paper proposes a low-complexity frequency-modulated continuous wave (FMCW) surveillance radar algorithm using random dual chirps in order to overcome the blind-speed problem and reduce the computational complexity. In surveillance radar algorithm, the most widely used moving target indicator (MTI) algorithm is proposed to effectively remove clutter. However, the MTI algorithm has a so-called ‘blind-speed problem’ that cannot detect a target of a specific velocity. In this paper, we try to solve the blind-speed problem of MTI algorithm by randomly selecting two beat signals selected for MTI for each frame. To further reduce the redundant complexity, the proposed algorithm first performs one-dimensional fast Fourier transform (FFT) for range detection and performs multidimensional FFT only when it is determined that a target exists at each frame. The simulation results show that despite low complexity, the proposed algorithm detects moving targets well by avoiding the problem of blind speed. Furthermore, the effectiveness of the proposed algorithm was verified by performing an experiment using the FMCW radar system in a real environment. Full article
(This article belongs to the Section Physical Sensors)
Show Figures

Figure 1

17 pages, 1376 KB  
Article
Estimating Speed and Direction of Small Dynamic Targets through Optical Satellite Imaging
by Greg Easson, Scott DeLozier and Henrique G. Momm
Remote Sens. 2010, 2(5), 1331-1347; https://doi.org/10.3390/rs2051331 - 7 May 2010
Cited by 16 | Viewed by 10961
Abstract
Moving Target Indicators (MTI) are systems used to distinguish movement from stationary scenes and sometimes to derive the spatial attributes of these objects. These systems are currently used in many sectors such as traffic studies, border surveillance, and military applications. The proposed MTI [...] Read more.
Moving Target Indicators (MTI) are systems used to distinguish movement from stationary scenes and sometimes to derive the spatial attributes of these objects. These systems are currently used in many sectors such as traffic studies, border surveillance, and military applications. The proposed MTI reveals vehicles and their velocities using commercial imagery from a passive optical satellite-mounted sensor. With simple process of image differencing, the MTI can automatically recognize conveyances in motion (speed and direction) represented by polygons formed by a group of pixels from successive images. Micro-change detection with an existing commercial satellite requires special considerations of differences in spatial and spectral resolution between images. Complications involving the movement detection system such as vehicle overlap, vehicle clusters, and zones of low confidence are refined by adding error-reducing modules. This process is tested on a variety of vehicles, their concentrations, and environments, confirming the feasibility of utilizing an MTI with commercial optical satellite imagery for movement recognition and velocity estimation. Full article
Show Figures

Figure 1

Back to TopTop