Direction of Arrival Estimation Techniques for Passive Radar based 3D Target Localization

Ummenhofer, Martin; Köhler, Michael; Schell, Jochen; O’Hagan, Daniel

doi:10.1109/radar.2019.8835841

Cited by 15 publications

(8 citation statements)

References 11 publications

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“…PR measurements are applied directly to a Cartesian tracking stage based on the Kalman filter [22], to obtain the target location. The application of the Kalman filter to target tracking is common in PR [23][24][25]. The core of the tracker is a recurrent predictioncorrection process that is usually performed by stochastic filters.…”

Section: Target Trackingmentioning

confidence: 99%

Improved 2D Ground Target Tracking in GPS-Based Passive Radar Scenarios

Gómez-del-Hoyo

del-Rey-Maestre

Jarabo-Amores

et al. 2022

Sensors

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Global Positioning System (GPS) satellites offer promising opportunity for Passive Radar systems due to their global coverage and the availability of multiple satellites throughout the world. However, their low power at ground level limits system coverage. In this paper, a GPS based Passive Radar which exploits a single illumination source, and uses digital array processing for ground targets localization is presented. To face signal power problems, a processing scheme combining reconstructed reference signals, adaptive filtering techniques and spatial filtering is implemented. Conventional beamforming techniques are used to increase the level of the target echo before the detection stage, and high resolution DoA estimation techniques are applied to estimate targets azimuth. Ground target localization in local Cartesian space is performed taking into account the system geometry, range and azimuth information. Both synthetic and real radar data are used to analyse system operation. During the measurement campaign, a cooperative vehicle was used for validation purposes. Results confirm that ground targets detection and localization are feasible using a single GPS transmitter.

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Section: Target Trackingmentioning

confidence: 99%

Improved 2D Ground Target Tracking in GPS-Based Passive Radar Scenarios

Gómez-del-Hoyo

del-Rey-Maestre

Jarabo-Amores

et al. 2022

Sensors

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“…The time difference of arrival (TDOA) measurement method for finding a target position has been widely used in the presence of multiple transmitters or multiple receivers [21][22][23][24]. The main target localization method used for bistatic passive radar is based on the measurements of bistatic range and direction of arrival (DOA) [25][26][27][28][29][30][31]. Different from the beamforming-based DOA estimation technique, a 2-D interferometric approach is exploited to estimate the DOA of the target echo in this paper.…”

Section: Signal Model For Target Detection and Localizationmentioning

confidence: 99%

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

Zhu¹,

Wang²,

Liu

2021

Wireless Communications and Mobile Computing

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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.

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“…Track initialisation was tested, for example, using maximum likelihood estimation [24–26]. With direction of arrival information, track accuracy can be improved and even the number of needed bistatic ranges can be decreased for the aircraft location [27]. Shu et al.…”

Section: Introductionmentioning

confidence: 99%

“…Track initialisation was tested, for example, using maximum likelihood estimation [24][25][26]. With direction of arrival information, track accuracy can be improved and even the number of needed bistatic ranges can be decreased for the aircraft location [27]. Shu et al [28] constructed two classes of tracks, a high-precision track and a low-precision track, for both track initialisation and track maintenance stages.…”

Section: Introductionmentioning

confidence: 99%

Directional sensitivity of track initialisation of a multistatic Doppler‐only passive radar network

Tolonen

Kauranne

Hartikka

et al. 2021

IET Radar Sonar & Navi

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A multistatic passive radar network originally presented in Ptak et al. for long-distance aircraft tracking is sensitive to track initialisation errors. When these errors exceed 50 km, target tracking often diverges. Initialisation can be improved by even coarse directional information. The impact of binary directional information was studied, which allows flights to be assigned to start from east or west of the multistatic network. Substantial improvement to the performance of flight tracking is observed on reference data based on Automatic Dependent Surveillance-Broadcast information.

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Direction of Arrival Estimation Techniques for Passive Radar based 3D Target Localization

Cited by 15 publications

References 11 publications

Improved 2D Ground Target Tracking in GPS-Based Passive Radar Scenarios

Improved 2D Ground Target Tracking in GPS-Based Passive Radar Scenarios

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

Directional sensitivity of track initialisation of a multistatic Doppler‐only passive radar network

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