Ambiguity function of Inmarsat BGAN signal for radar application

Lyu, Xiaoyong; Stove, A.G.; Gashinova, Marina; Cherniakov, M.

doi:10.1049/el.2016.1400

Cited by 11 publications

(6 citation statements)

References 4 publications

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“…We assume in the paper that signals from different transmitters are resolvable. This is applicable for many communication signals such as the FM and many satellite signals [14], [40], [41].…”

Section: Target Tracking Problem Definitionmentioning

confidence: 99%

Sequential Multi-Sensor JPDA for Target Tracking in Passive Multi-Static Radar With Range and Doppler Measurements

Lyu

Wang

2019

IEEE Access

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Target tracking in passive multi-static radar (PMSR) with bistatic range and Doppler frequency measurements from multiple transmit-receive pairs is gaining increasing interest. For the data association problem in this scenario, the parallel architecture of a multi-sensor joint probabilistic data association (P-MSJPDA) filter has been significantly investigated. As an alternative architecture, the sequential MSJPDA (S-MSJPDA) is rarely discussed in PMSR. In this paper, we evaluate the behaviors of S-MSJPDA in PMSR target tracking with bistatic range and Doppler frequency measurements. A comprehensive comparison between the S-MSJPDA and the P-MSJPDA in PMSR is provided. It can be found from the analysis that S-MSJPDA outperforms its parallel counterpart in terms of computational efficiency, given an acceptable degradation in position accuracy. The S-MSJPDA is further applied to an experimental passive multi-static radar for aircrafts tracking. The real data results obtained are rather close to the true trajectories of the targets. This demonstrates that the S-MSJPDA has great potentials in PMSR target tracking. INDEX TERMS Passive multi-static radar, target tracking, multi-sensor joint probabilistic data association.

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Section: Target Tracking Problem Definitionmentioning

confidence: 99%

Sequential Multi-Sensor JPDA for Target Tracking in Passive Multi-Static Radar With Range and Doppler Measurements

Lyu

Wang

2019

IEEE Access

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“…Ambiguity function has the characteristics of high resolution and strong clutter suppression ability, and can deal with non-stationary signals very well. Many scholars have used it to study radar Symmetry 2018, 10, 730 8 of 14 signals [24][25][26]. Correlation coefficient is a good way to measure the similarity of two signals, and it is simple in computation.…”

Section: Ambiguity Correlation Theorymentioning

confidence: 99%

Rolling Bearing Fault Diagnosis Based on EWT Sub-Modal Hypothesis Test and Ambiguity Correlation Classification

Wang

et al. 2018

Symmetry

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Because of the cyclic symmetric structure of rolling bearings, its vibration signals are regular when the rolling bearing is working in a normal state. But when the rolling bearing fails, whether the outer race fault or the inner race fault, the symmetry of the rolling bearing is broken and the fault destroys the rolling bearing's stable working state. Whenever the bearing passes through the fault point, it will send out vibration signals representing the fault characteristics. These signals are often non-linear, non-stationary, and full of Gaussian noise which are quite different from normal signals. According to this, the sub-modal obtained by empirical wavelet transform (EWT), secondary decomposition is tested by the Gaussian distribution hypothesis test. It is regarded that sub-modal following Gaussian distribution is Gaussian noise which is filtered during signal reconstruction. Then by taking advantage of the ambiguity function superiority in non-stationary signal processing and combining correlation coefficient, an ambiguity correlation classifier is constructed. After training, the classifier can recognize vibration signals of rolling bearings under different working conditions, so that the purpose of identifying rolling bearing faults can be achieved. Finally, the method effect was verified by experiments.using wavelet transform. Reference [14] mainly studies the fault diagnosis of local defects of rolling bearings based on wavelet feature extraction. In Reference [15], the feature of rolling bearing signals is extracted by using the time bound integral of continuous wavelet transform coefficient. But wavelet decomposition is constrained by wavelet basis functions [14][15][16], and the number of decomposition layers and thresholds of wavelets will affect the noise filtering effect during noise filtering [13,16]. Empirical mode decomposition (EMD) is a very good method for analyzing non-stationary signals, which enjoys many applications in fault diagnosis of rolling bearings [17,18]. However, EMD has problems such as modal mixture and endpoint effects [19,20]. Combining EMD's adaptability and theoretical framework of wavelet analysis, Gilles proposed a new signal processing method, namely empirical wavelet transform (EMT) [21]. The method adaptively divides the signal frequency spectrum into several frequency bands by extracting maximum value point of the frequency domain, and constructs a suitable orthogonal wavelet filter bank to separate each frequency band. Each separated frequency band corresponds to a signal in the time domain. This signal is referred to as a modal of the original signal. This method avoids the problems of EMD modal in aliasing and endpoint effects, while inheriting the strength of EMD and wavelet analysis methods, thus it is a very good method for processing non-stationary signals.According to the above analysis, we propose a novel rolling bearing fault diagnosis method based on an empirical wavelet transform (EWT) sub-modal hypothesis test and ambiguity correlation classification....

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“…For radar imaging it is important that the signals have suitable correlation properties [5,6]. Figure 3 shows example results for the Inmarsat class 5 L-band signals (bandwidth approximately 190 MHz).…”

Section: Available Broadcast Signalsmentioning

confidence: 99%

Feasibility of Passive Bistatic Geosynchronous Radar Using Comsat Transmissions

Hobbs

Convenevole

Gashinova

et al. 2018

IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium

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Communication satellites in geosynchronous orbit are increasingly broadcasting digital signals with high bandwidth and high power. These signals are in principle well-suited to radar imaging and the study presented here is an initial feasibility study for a passive bistatic synthetic aperture radar using satellites in geosynchronous orbit (GEO). The persistent viewing possible from GEO could enable important new applications. The mission concept is outlined and studies of the available signal formats identify digital TV broadcasts in Ku-band as most suitable for radar imaging. The additional space hardware required is a dedicated receive channel, which could be implemented as a hosted payload at modest cost. Our findings so far suggest that the mission concept is feasible for coarse spatial resolution images and that it could therefore provide a low-cost technology demonstration of geosynchronous radar.

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Ambiguity function of Inmarsat BGAN signal for radar application

Cited by 11 publications

References 4 publications

Sequential Multi-Sensor JPDA for Target Tracking in Passive Multi-Static Radar With Range and Doppler Measurements

Sequential Multi-Sensor JPDA for Target Tracking in Passive Multi-Static Radar With Range and Doppler Measurements

Rolling Bearing Fault Diagnosis Based on EWT Sub-Modal Hypothesis Test and Ambiguity Correlation Classification

Feasibility of Passive Bistatic Geosynchronous Radar Using Comsat Transmissions

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