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RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

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Updated: Jun 27, 2026

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Monostatic Waveform-Domain Passive Radar for Detection and Localization Using a Sparse Circular Array with

Vladimir Volman¹, James A Nessel¹

¹National Aeronautics and Space Administration (NASA) Glenn Research Center, Cleveland, OH 44135, USA.

Sensors (Basel, Switzerland)

|June 26, 2026

Summary

This summary is machine-generated.

The RaDICAL framework enables passive radar target detection and localization using sparse arrays and multifrequency dither. This approach achieves reliable sensing at low signal-to-noise ratios, supporting compact, reference-free passive sensing systems.

Keywords:

deterministic multifrequency dither frequency-diverse arrays illuminators of opportunity passive RF sensing passive radar sparse uniform circular array (SUCA)waveform dictionary matching waveform-domain sensing

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Area of Science:

Radar Systems Engineering
Signal Processing
Electromagnetics

Background:

Passive radar systems offer covert and cost-effective surveillance solutions.
Traditional passive radar methods often require explicit estimation of target parameters like Doppler or time delays.
Sparse array antennas and advanced waveform processing are key areas for improving passive radar performance.

Purpose of the Study:

To introduce the RaDICAL (Radar Detection via Composite Information Domain Array Localization) monostatic passive radar framework.
To enable joint target detection and localization without explicit parameter estimation.
To leverage sparse uniform circular arrays (SUCA) and multifrequency dither for enhanced passive sensing.

Main Methods:

Developed a SUCA-based signal model for point and extended targets.
Formulated detection and localization as a waveform-domain dictionary matching problem.
Employed normalized complex correlation and QR-domain processing for hypothesis testing.
Utilized multifrequency dither to create distinctive composite receiver waveforms.

Main Results:

Demonstrated that multifrequency dither yields separable composite waveforms with stable recognition performance.
Achieved reliable target detection at input signal-to-noise ratios (SNR) of -10 to 0 dB.
Showcased feasible detection and localization with modest illuminator effective isotropic radiated power (EIRP) and compact receivers.
Validated performance through Monte Carlo simulations evaluating waveform separability, ROC, and localization accuracy.

Conclusions:

The RaDICAL framework supports compact, reference-free passive sensing for joint target detection and localization.
Waveform-domain processing with multifrequency dither offers a robust alternative to explicit parameter estimation.
The proposed method shows promise for practical implementation in various passive radar applications.