Marine Target Localization with Passive GNSS-Based Multistatic Radar: Experimental Results

Antoniou, Michail; Stove, A.G.; Tzagkas, Dimitrios; Cherniakov, M.; Ma, Hongguang

doi:10.1109/radar.2018.8557331

Cited by 9 publications

(4 citation statements)

References 11 publications

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“…In 2018, the University of Birmingham in the United Kingdom proposed a theoretical framework for moving target positioning based on bistatic distance measurement which gave prediction accuracy. Positioning is achieved through multidelay technology and has been verified by experiments [6,7]. Fabrizio Santi et al proposed increasing the integration time to improve ship detection capability [8].…”

Section: Introductionmentioning

confidence: 94%

“…1 ○ Assume that the weak signal is received by the No.1 satellite, and the strong signal that needs to cancel the noise is received by the No.2 satellite. The signal Equation are expressed as ( 6) and (7), where the amplitude and code phase of the No. 1 and No.2 satellites are A 1 , A 2 and P N 1 (t), P N 2 (t) respectively, the doppler frequency are cos(ω 1 t), cos(ω 2 t),i represents the satellite number of any other satellite, r(t) represents the received signal,P N (t) represents the pseudorandom code,n(t) represents the simulated signal noise, and t is the acquisition time.…”

Section: Rdm Noise Reduction Algorithmmentioning

confidence: 99%

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Enhanced Range Doppler Mapping Algorithm for Passive GNSS based radar Rerial Target Detection

Zhang,

Zheng,

Zheng

et al. 2023

Preprint

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Passive GNSS based radar is a developing non-contact and emerging remote sensing technology in recent decade. However, due to the problems of weak signal and low resolution, the application of such technology in remote sensing application is very limited. This paper considers GNSS based radar detection of air object, and puts forward the signal-to-noise ratio improvement scheme of range doppler map (RDM) to improve the detection ability. In this paper, bi-static GNSS radar model is employed. The RDM of air target is obtained on the basis of direct and reflected signals. The proposed RDM SNR (signal-to-noise ratio) improvement algorithm mainly uses the autocorrelation characteristics of GNSS code to purify and reduce the noise of GNSS signal, so as to improve resolution of RDM and accuracy of target motion state solution. Compared with the current noise reduction method, which mostly depends on the prior conditions such as background environment, the proposed algorithm is more applicable, as it is mainly based on the characteristics of the signal. The RDM image is obtained by simulating moving target detection.In the condition of input signal CNR(Carrier-to-noise ration) is 35dB, the algorithm shows that the image information entropy after noise reduction is 63.23% for GPS signal and 71.69% for Beidou signal which lower than that before noise reduction.

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Section: Introductionmentioning

confidence: 94%

Section: Rdm Noise Reduction Algorithmmentioning

confidence: 99%

Enhanced Range Doppler Mapping Algorithm for Passive GNSS based radar Rerial Target Detection

Zhang,

Zheng,

Zheng

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Generally speaking, there are two main branches of global navigation satellite system (GNSS) remote sensing used for earth observation, i.e., GNSS reflectometry (GNSS-R) and GNSS Radio Occultation (GNSS-RO). Meanwhile, from the perspective of radar, employing GNSS signals as illuminators of space-surface synthetic aperture radar (SAR) and multistatic passive radar systems is also of great potential [1].…”

Section: Introduction Ince Globalmentioning

confidence: 99%

Moving Target Detection and Parameter Estimation Using BeiDou GEO Satellites-Based Passive Radar With Short-Time Integration

Zhang

Shi

Yan

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Owing to the global coverage and high visibility of global navigation satellite systems (GNSS), passive radar using GNSS satellites as transmitters of opportunity has shown great potential for moving target detection, and its possibility to detect short-range maritime targets has been verified. Nevertheless, the existing methods always require tens of seconds for echo integration, which is not ideal for the detection of targets with high maneuverability. To solve this problem, a bistatic configuration using BeiDou geostationary earth orbit (GEO) satellites as illuminators of opportunity, which is suited for short-time coherent integration of echo signals, is presented. In addition, the corresponding signal processing method is introduced. To achieve a more continuous trajectory of the target, a method used to fuse range-Doppler maps obtained individually from multiple BeiDou GEO satellites is also described. The effectiveness and functionality of our proposed algorithms are demonstrated with an experiment in which a ferry was used as a moving target and its real-time location data were adopted as a reference.

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“…Among these satellite constellations, the time difference of arrival (TDOA) location method is used to obtain the target position. The long-term moving target indicator (MTI) processing of merchant ships is realized, and the detection distance can achieve 3 km [4][5][6]. Table 1 indicates that the detection distance is very close, and the application scenarios are very limited.…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation for Uniformly Accelerating Moving Target in the Forward Scatter Radar Network

Zheng

et al. 2022

Remote Sensing

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Passive radar based on the global navigation satellite positioning system (GNSS) has become the focus of attention in the field of radar. A parameter estimation method is proposed in the forward scatter radar (FSR) network based on GNSS to extend the application scenarios. For uniformly accelerating moving targets, only the instant times when the target crosses the individual baselines are used to retrieve the target motion parameters. The target position, velocity, and acceleration information can be obtained. Firstly, the minimum network configuration is derived theoretically. Then, the effects of crossing time error, station location error, transmitting/receiving station deployment, and target height on the accuracy are analyzed through Monte Carlo simulations. Finally, the simulation results indicate that the target position estimation error is in the order of 100 m. This paper provides the fundamental theory of aerial target positioning with a GNSS-based FSR network.

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Marine Target Localization with Passive GNSS-Based Multistatic Radar: Experimental Results

Cited by 9 publications

References 11 publications

Enhanced Range Doppler Mapping Algorithm for Passive GNSS based radar Rerial Target Detection

Enhanced Range Doppler Mapping Algorithm for Passive GNSS based radar Rerial Target Detection

Moving Target Detection and Parameter Estimation Using BeiDou GEO Satellites-Based Passive Radar With Short-Time Integration

Parameter Estimation for Uniformly Accelerating Moving Target in the Forward Scatter Radar Network

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