A Novel Method to Detect and Localize LPI Radars

Hejazikookamari, Farzam; Norouzi, Yaser; Kashani, E. S.; Nayebi, Mohammad Mahdi

doi:10.1109/taes.2018.2885109

Cited by 19 publications

(14 citation statements)

References 23 publications

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“…A similar argument holds for the nearest cell to the i th cell in y-direction and it can be reasoned that if ∆y ∝ k λr min D then a i and a j are almost uncorrelated. These results are consistent with the image resolution derivation in azimuth and range directions derived in [24], in which it is proved the resolution of the proposed imaging method in both azimuth and range directions are in proportion to λr min D if the sensor moves along a straight line. To sum up, we argue that if the moving platform proceeds in a straight line and samples the phase difference regularly, then the feasibility of the recovery of PUs locations depends on λr min D .…”

Section: A Survay On Matrix Asupporting

confidence: 90%

“…, which meansS i is narrow-band, the remaining time-varying terms in (5) are exponential phase differences and channel gains (α i (t)), these terms change very slowly in the time domain and can be considered constant in a short period of time (e.g. a second) [24]; therefore the expectation task in Figure 2 is not distorted by the timevarying nature of E{z 1 (t)z * 2 (t)}. To find the potential PUs presented in a square area of interest we assume n × n identical and equally spaced cells cover the whole area, and there can be only a maximum of one PU located in each cell.…”

Section: Problem Formulationmentioning

confidence: 99%

“…A method similar to the Synthetic Aperture Radar (SAR) imaging technique introduced to passively detect and localize very low power PUs [23]. The proposed method suggest that the phase difference between received signals of two distant antennas mounted on a moving platform can be applied to find locations of unknown emitters in an area of interest [24], [25]. Using the same setup, we expand the results to multiple sources localization suggesting a simple receiver that uses a sparse recovery algorithm for the source localization task.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Wireless Source Localization Utilizing An Airborne Interfrometry

Hejazi¹,

Joneidi²,

Rahnavard³

2021

Preprint

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This paper investigates the problem of localization of co-channel transmitters or primary users (PUs) using an array mounted on a moving aerial platform. As a practical alternative for a sensor network to pursue the localization task, the proposed Phase Interferometric Source Localization (PISL) technique utilizes a moving sensor that measures phase difference between two antennas mounted on the platform. Due to the sparse nature of PUs' distribution in the region, we model the localization task as a simple basis-pursuit denoising framework and introduce a reconstruction method using a sparse recovery algorithm to discover locations of unknown PUs based on the phase difference measurements. We show that the ratio of distance between two antennas to the carrier-frequency wavelength is the critical parameter making the localization feasible. We also propose a scheme for sensor motion design in order to maximize the number of detectable PUs based on mutual coherence property. Since the motion optimization problem is very hard to address we develop a simple geometric relaxation to address the problem. The simulation results show that PISL can precisely recover the map of PUs with only few measurements and also reveal that sensor motion path can have determinate effect on the localization accuracy. PISL performance is compared with an state-of-the-art technique that utilizes adaptive beamforming and results show the superiority of PISL results in localization accuracy.

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Section: A Survay On Matrix Asupporting

confidence: 90%

Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Wireless Source Localization Utilizing An Airborne Interfrometry

Hejazi¹,

Joneidi²,

Rahnavard³

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…These systems allow instantaneous target position measurement but only if the condition of simultaneous irradiation of all the ESM receivers [ 14 ] of the localization system is satisfied. However, localization of Low Probability of Intercept (LPI) targets [ 15 , 16 ], especially in military applications, can be problematic in these systems. One of the features of the LPI signal emitters (radars) is a side lobes suppression of their antenna patterns.…”

Section: Introductionmentioning

confidence: 99%

Radar Position Estimation by Sequential Irradiation of ESM Receivers

Hubacek

Veselý

Olivová

2021

Sensors

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In this article, a new technique for determination of 2D signal source (target) position is proposed. This novel approach, called the Inscribed Angle (InA), is based on measuring the time difference of sequential irradiation by the main beam of the target antenna’s radiation pattern, using Electronic Support Measures (ESM) receivers, assuming that the target antenna is rotating and that its angular velocity is constant. In addition, it is also assumed that the localization system operates in a LOS (Line of Sight) situation and that three time-synchronized sensors are placed arbitrarily across the area. The main contribution of the article is a complete description of the proposed localization method. That is, this paper demonstrates a geometric representation and an InA localization technique model. Analysis of the method’s accuracy is also demonstrated. The time of irradiation of the receiving station corresponds to the direction in which the maximum received signal strength (RSS) was measured. In order to achieve a certain degree of accuracy of the proposed positioning technique, a method was derived to increase the accuracy of the irradiation time estimation. Finally, extensive simulation was conducted to demonstrate the performance and accuracy of our positioning method.

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“…Lately, methods that use a combination of two or three of AOA/TDOA/FDOA techniques have gained more attention [9], [10]. Phase interferometry is widely used in electronic warefere applications for wide-band (WB) interferometric direction finding [11], [12], [13]. Since phase difference between two antennas introduces ambiguous DOAs, most techniques proposed in the literature suggest using two or more baselines to disambiguate phase difference [14], [15].…”

Section: Introductionmentioning

confidence: 99%

A Tensor-based Localization Framework Exploiting Phase Interferometry Measurements

Hejazi¹,

Joneidi²,

Rahnavard³

2020

Preprint

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In this paper, a framework for localization of multiple co-channel transmitters using phase difference measurements between two antennas mounted on sensors of a sensor network is proposed. To pursue localization, we equip each sensor with two antennas and we use temporal cross-correlations between the received signals of the two antennas to extract the phase differences between each antenna pairs, named as phase interferometry measurements (PIMs), provoked by each transmitters using tensor decomposition. We calculate Cramer-Rao lower bound of error of localization using PIMs. Our simulation results show that highly accurate estimations can be achieved using PIMs. We also compare the accuracy of our proposed technique with a sensor network that exploits highly directional linear array antennas and show that our proposed technique can perform similar to a network that employs very large antenna arrays.

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A Novel Method to Detect and Localize LPI Radars

Cited by 19 publications

References 23 publications

Wireless Source Localization Utilizing An Airborne Interfrometry

Wireless Source Localization Utilizing An Airborne Interfrometry

Radar Position Estimation by Sequential Irradiation of ESM Receivers

A Tensor-based Localization Framework Exploiting Phase Interferometry Measurements

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