Multiemitter Two-Dimensional Angle-of-Arrival Estimator via Compressive Sensing

Wu, Chen; Elangage, Janaka

doi:10.1109/taes.2019.2958397

Cited by 13 publications

(17 citation statements)

References 39 publications

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“…[ 36 , 37 ] give some examples. Recently, Wu et al [ 38 , 39 ] introduced a new multi-emitter 2D AoA estimator from 2–18 GHz based on signal spatial-sparsity [ 40 ] and Dantzig Selector [ 41 ] methods. The key features of the estimator are no requirement of a priori knowledge of intercepted signals, including signal frequencies, and its capability of processing multiple simultaneous incoming signals within the 2D array field-of-view (FOV) and the instantaneous bandwidth of microwave digital receivers.…”

Section: Introductionmentioning

confidence: 99%

“…The key features of the estimator are no requirement of a priori knowledge of intercepted signals, including signal frequencies, and its capability of processing multiple simultaneous incoming signals within the 2D array field-of-view (FOV) and the instantaneous bandwidth of microwave digital receivers. A good summary of the current CS-based AoA methods, including Bayesian CS for direction-of-arrival estimation [ 42 , 43 ], is also given in [ 39 ].…”

Section: Introductionmentioning

confidence: 99%

“…To develop the CS-based AoA measurement system introduced in [ 39 ] with the considerations of using the system in RESM for radar electronic warfare (REW) applications, this article presents the research results of (1) the AoA estimation system hardware implementation, (2) the open lab-based AoA measurement setup, (3) the system-level RF high-fidelity modeling and simulation (RF HF-M&S), and (4) measurement and simulation results. More specifically, the article presents the following in detail: A 6-channel 2–18 GHz RF/digital receiver hardware, using PXIe form-factor, integrated with a 6-element 2–18 GHz cavity-backed-spiral-antenna (CBSA) array with randomly located element positions given in [ 39 ]; To demonstrate that the CS-based AoA method introduced in [ 39 ] can be used in dynamic REW engagement environment, the RF HF-M&S approach was used to model: An engagement scenario in the System Tool Kit (STK) [ 44 ] with a ground-based S-band target acquisition radar (TAR) and an aircraft equipped with a RESM system that has the CS-based AoA measurement capability; The S-band radar transmitting system behavioral model in SystemVue (SVE) [ 45 ]; A 6-channel microwave-digital receiving system behavioral model in SVE, and The CS-based AoA algorithm [ 39 ] in Matlab. The measurement setup for AoA lab test from 2 to 18 GHz, and Measurement and simulation results.…”

Section: Introductionmentioning

confidence: 99%

“…A 6-channel 2–18 GHz RF/digital receiver hardware, using PXIe form-factor, integrated with a 6-element 2–18 GHz cavity-backed-spiral-antenna (CBSA) array with randomly located element positions given in [ 39 ];…”

Section: Introductionmentioning

confidence: 99%

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Hardware Implementation and RF High-Fidelity Modeling and Simulation of Compressive Sensing Based 2D Angle-of-Arrival Measurement System for 2–18 GHz Radar Electronic Support Measures

Krishnasamy

Elangage

2021

Sensors

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This article presents the hardware implementation and a behavioral model-based RF system modeling and simulation (M&S) study of compressive sensing (CS) based 2D angle-of-arrival (AoA) measurement system for 2–18 GHz radar electronic support measures (RESM). A 6-channel ultra-wideband RF digital receiver was first developed using a PXIe-based multi-channel digital receiver paired with a 6-element random-spaced 2D cavity-backed-spiral-antenna array. Then the system was tested in an open lab environment. The measurement results showed that the system can measure AoA of impinging signals from 2–18 (GHz) with overall RMSE of estimation at 3.60, 2.74, 1.16, 0.67 and 0.56 (deg) in L, S, C, X and Ku bands, respectively. After that, using the RF high-fidelity M&S (RF HF-M&S) approach, a 6-channel AoA measurement system behavioral model was also developed and studied using a radar electronic warfare (REW) engagement scenario. The simulation result showed that the airborne AoA measurement system could successfully measure an S-band ground-based target acquisition radar signal in the dynamic REW environment. Using the RF HF-M&S model, the applicability of the system in other frequencies within 2–18 (GHz) was also studied. The simulation results demonstrated that the airborne AoA measurement system can be used for 2–18 GHz RESM applications.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Hardware Implementation and RF High-Fidelity Modeling and Simulation of Compressive Sensing Based 2D Angle-of-Arrival Measurement System for 2–18 GHz Radar Electronic Support Measures

Krishnasamy

Elangage

2021

Sensors

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“…The information can be obtained from time, bearing, power, and, more recently, channel related measurements. Some examples include the time of arrival (TOA) [13,14], angle of arrival (AOA) [15,16], received signal strength (RSS) [17,18], and channel state information (CSI) [19,20]. These signal related measurements can be employed independently or combined with different levels of accuracy [21,22].…”

Section: Introductionmentioning

confidence: 99%

Fundamental Limitations and State-of-the-art Solutions for Target Node Localization in WSNs

Najarro¹,

Song²,

Kim³

2021

Preprint

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With the advances in new technological trends and the reduction in prices of sensor nodes, wireless sensor networks (WSNs) and their applications are proliferating in several areas of our society such as healthcare, industry, farming, and housing. Accordingly, in recent years attention on localization has increased significantly since it is one of the main facets in any WSN. In a nutshell, localization is the process in which the position of any sensor node is retrieved by exploiting measurements from and between sensor nodes. Several techniques of localization have been proposed in the literature with different localization accuracy, complexity, and hence different applicability. The localization accuracy is limited by fundamental limitations, theoretical and practical, that restrict the localization accuracy regardless of the technique employed in the localization process. In this paper, we pay special attention to such fundamental limitations from the theoretical and practical points of view and provide a comprehensive review of the state-of-the-art solutions that deal with such limitations. Additionally, discussion on the theoretical and practical limitations together with their recent solutions, remaining challenges, and perspectives are presented.

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High sensitivity multi‐channel digital receiver for wideband very weak signal direction‐finding classified by machine learning

Wu,

Low

2024

IET Radar Sonar & Navi

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For weak signal detection with direction‐finding (DF), this article presents a new receiver design approach that combines our accumulatively increasing receiver sensitivity (AIRS) signal detection algorithm with the compressive‐sensing (CS)‐based DF‐array/algorithm. The former uses the concept of timeslot (TS)‐based signal threshold detection, whereas the latter employs a frequency‐independent array with randomly located elements, whose bandwidth (BW) largely determines the DF‐array BW. To estimate the direction of a signal, the AIRS algorithm generates the array steering vectors in each TS when the amplitude of any frequency bins exceeds the predetermined threshold of the TS. The aim of this paper is to demonstrate the ability of the new receiver to detect low probability of intercept radar signals with high DF accuracy, fine frequency resolution, and good time‐of‐arrival measurement resolution. To discriminate accurate emitter directions from many false estimations created by the DF‐array in very low signal‐to‐noise ratio environments, K‐means clustering was also applied. In a scenario, the frequency modulated signals from several 165‐mW X‐band radars were in the field of view of a 6‐element DF‐array. Simulation results show that the receiver can accurately estimate all the emitters' directions with root mean squared error of less than 1°, when the separation between the DF‐array and radars is about 100 km.

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Multiemitter Two-Dimensional Angle-of-Arrival Estimator via Compressive Sensing

Cited by 13 publications

References 39 publications

Hardware Implementation and RF High-Fidelity Modeling and Simulation of Compressive Sensing Based 2D Angle-of-Arrival Measurement System for 2–18 GHz Radar Electronic Support Measures

Hardware Implementation and RF High-Fidelity Modeling and Simulation of Compressive Sensing Based 2D Angle-of-Arrival Measurement System for 2–18 GHz Radar Electronic Support Measures

Fundamental Limitations and State-of-the-art Solutions for Target Node Localization in WSNs

High sensitivity multi‐channel digital receiver for wideband very weak signal direction‐finding classified by machine learning

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