Bistatic Radar Research Articles

A Coherent Integration Method for Moving Target Detection in Frequency Agile Signal-Based Passive Bistatic Radar

In this paper, the possibility of improving target detection performance in passive bistatic radar by exploiting a frequency agile (FA) signal is investigated, namely frequency agile signal-based passive bistatic radar (FAPBR) coherent integration. Since the carrier frequency of each pulse signal is agile, FAPBR coherent integration suffers from the problems of random range and Doppler phase fluctuations. To tackle these challenges, a novel FA signal coherent integration target detection scheme for PBR is proposed. In particular, the phase quadratic difference principle is presented for eliminating Doppler phase hopping. Then, frequency rearrangement is adopted to compensate for random range phase fluctuation while obtaining the high-range-resolution profiles (HRRPs) of the detecting target. Further, we innovatively present a sliding-range ambiguity decoupling (S-RAD) method to remove the range ambiguity effect in the case of the high pulse repetition frequency (HPRF). Compared with the existing methods, the proposed method can effectively mitigate Doppler phase hopping without requiring prior target velocity information, offering improved coherent integration performance in frequency agile signals with reduced computational complexity. Moreover, it successfully corrects the range ambiguity issue caused by HPRF. Finally, a series of simulation results are presented to demonstrate the effectiveness of the proposed algorithm.

An Improved NLCS Algorithm Based on Series Reversion and Elliptical Model Using Geosynchronous Spaceborne–Airborne UHF UWB Bistatic SAR for Oceanic Scene Imaging

Geosynchronous spaceborne–airborne (GEO-SA) ultra-high-frequency ultra-wideband bistatic synthetic aperture radar (UHF UWB BiSAR) provides high-precision images for marine and polar environments, which are pivotal in glacier monitoring and sea ice thickness measurement for polar ocean mapping and navigation. Contrasting with traditional high-frequency BiSAR, it faces unique challenges, such as the considerable spatial variability, significant range–azimuth coupling, and vast volumes of echo data, which impede high-resolution image reconstruction. This paper presents an improved bistatic nonlinear chirp scaling (NLCS) algorithm for imaging oceanic scenes with GEO-SA UHF UWB BiSAR. This methodology extends the two-dimensional (2-D) spectrum up to the sixth order via the method of series reversion (MSR) to meet accuracy demands and then employs an elliptical model to elucidate the alterations in the azimuth frequency modulation (FM) rate mismatch. Initially, the imaging geometry and signal model are introduced, and then a separation of bistatic slant ranges based on the configuration is proposed. In addition, during range processing, after eliminating linear range cell migration (RCM), the derivation process for the sixth-order 2-D spectrum is detailed and an improved filter is applied to correct the high-order RCM. Finally, during azimuth processing, the causes of the FM rate mismatch are analyzed, a cubic perturbation function derived from the elliptical model is used for FM rate equalization, and a unified sixth-order filter is applied to complete the azimuth compression. Experimental results with point targets and natural oceanic scenes validate the outstanding efficacy of the proposed NLCS algorithm, particularly in imaging quality enhancements for GEO-SA UHF UWB BiSAR.

Analysis of bistatic multiphoton quantum radar cross section for the cylindrical surface.

A closed-form model of bistatic multiphoton quantum radar cross section (QRCS) for the cylindrical surface, the main structure of typical aircraft, especially missiles, is established to analyze the system and scattering characteristics. The influence of curvature of the three-dimensional target on QRCS is analyzed. By comparing and analyzing the bistatic multiphoton QRCS for a cylinder and a rectangular plate, we find that the QRCS for the convex surface target is the extension of the QRCS for the planar target with inhomogeneous atomic arrangement intervals and patterns. The characteristics of cylindrical QRCS are discussed by combining the transceiver system and the photon number of the transmitted signal, and the influences of the cylindrical radius, cylindrical length, and incident photon number on QRCS are analyzed. The bistatic results provide guidance on potential strong scattering directions for the target under various directions of photon incidence. Compared with the plane target, the cylindrical target amplifies scattering intensity near the target surface at the scattering angle side in the bistatic system. A bistatic multiphoton quantum radar system can achieve sharpening and amplification of the main lobe of the QRCS for a cylinder in an extensive scattering angle range. Bistatic multiphoton quantum radar has better visibility for the cylinder with a smaller length. These characteristics will provide prior information for research in many fields, such as photonic technology, radar technology, and precision metrology.

Applications of the Symmetrical Structures of Cassini Ovals

One of the geometric figures that has symmetry properties is the Cassini oval. The Cassini oval is a curve defined as the locus of points in the plane such that the product of the distances to two fixed points is constant. Cassini ovals are named after the astronomer Giovanni Domenico Cassini, who studied them in 1680. Today, the geometric properties of Cassini ovals are used in many fields: analytical geometry, nuclear physics, radiolocation, and industrial applications. The bistatic radar uses Cassini ovals to detect various targets in radiolocation. Until now, there have been no studies on the clustering capabilities of Cassini ovals. As a novelty, it is hypothesized that clustering possibilities could be used for Cassini ovals. In this article, a study of the capabilities of Cassini ovals in radiolocation was carried out, and their suitability for clustering purposes was shown.

Unmanned Airborne Bistatic Interferometric Synthetic Aperture Radar Data Processing Method Using Bi-Directional Synchronization Chain Signals

The bistatic Interferometric Synthetic Aperture Radar (InSAR) system can overcome the physical limitations imposed by the baseline of monostatic dual-antenna InSAR. It provides greater flexibility and can enhance elevation measurement accuracy through a well-designed baseline configuration. Unmanned aerial vehicles (UAVs) equipped with bistatic InSAR, having relatively low cost and high flexibility, are useful for mapping and land resource exploration. However, due to challenges including spatiotemporal synchronization and motion errors, there are limited reports on UAV-borne bistatic InSAR. This paper proposes a comprehensive method for processing data from small UAV-borne bistatic InSAR by integrating two-way synchronization chain signals. The proposed method includes compensation for time and phase synchronization errors, trajectory refinement with synchronized chain and Position and Orientation System (POS) data, high-precision bistatic InSAR imaging, and interferometric processing. Height inversion results based on the proposed method are also provided, which demonstrate the effectiveness of the proposed method in improving the accuracy of interferometric measurement at calibration points from 0.66 m to 0.42 m.

Angle estimation based on Vandermonde constrained CP tensor decomposition for bistatic MIMO radar under spatially colored noise

We address the problem of Vandermonde constrained CANDECOMP/PARAFAC (CP) tensor decomposition in application to angle estimation for bistatic multiple-input multiple output (MIMO) radar under spatially colored noise. By exploiting the temporally uncorrelated characteristic of colored noise, a new denoising scheme based on the temporally smoothed cross-correlation approach is presented. Then, after rearranging the smoothed cross-correlation matrix into a fourth-order tensor, a Vandermonde constrained CP tensor decomposition model is formulated, which fully exploits the multidimensional structure of the array measurement and the Vandermonde structure of the factor matrices. To solve this model, an efficient constrained alternating least squares (ALS) algorithm is developed to decompose the Vandermonde factor matrices. Finally, joint estimates of direction of departure (DOD) and direction of arrival (DOA) are obtained by the generators of the Vandermonde factor matrices. Compared with the state-of-the-art approaches, the proposed method can achieve better angle estimation performance by jointly using the temporally smoothed cross-correlation denoising operation and enforcing the Vandermonde structure information in the tensor decomposition. Numerical simulation results verify the effectiveness and improvement of our algorithm.

Interference Suppression for an FM-Radio-Based Passive Radar via Deep Convolutional Autoencoder

Recently, the passive bistatic radar (PBR) which exploits frequency modulation (FM) radio transmitters as illuminators, has witnessed widespread usage owing to its various advantages. However, the characteristics of FM-radio-based PBR result in interference components in the range–Doppler (RD) map, which may increase false alarms. Therefore, this study proposes a method for suppressing interference components using a deep learning approach. The two main contributions of this study are as follows. First, a convolutional autoencoder model capable of effectively suppressing interference in the RD map of PBR was proposed. Second, a synthetic RD map dataset generation method that can enable the autoencoder to operate robustly in PBR in a real environment was presented. Further, a performance comparison between the proposed method and existing methods using simulated data proved that the deep learning-based method exhibited superior target detection performance. Furthermore, using the data recorded by the PBR in a real environment, the proposed autoencoder model was shown to effectively suppress interference components in a real interference environment.

Average effective subcarrier-domain sparse representation approach for target information estimation in CP-OFDM-based passive bistatic radar

Although some existing sparse representation (SR) methods are robust for target detection in passive bistatic radar (PBR), they still face the challenges of high computational complexity and poor detection performance for extremely low-signal-to-clutter ratio (SCR) target. So, an average effective subcarrier (AES)-domain sparse representation approach is investigated in this paper. Firstly, the AES-based SR model is proposed to solve the problem of high computational complexity, which is established by utilizing the sparseness of the orthogonal frequency-division multiplexing (OFDM) with cyclic prefix (CP) signals in each effective subcarrier domain. Then, considering the difficulty of detecting extremely low-SCR targets, clutter cancellation is implemented by the SR-based optimization model. Two AES-S algorithms, namely AES-S-based clutter cancellation in the time domain (AES-S-T) and AES-S-based clutter cancellation in the subcarrier domain (AES-S-C), are proposed, and the computational complexity is further reduced. Finally, extensive simulation and experimental results illustrate that the proposed algorithms have good detection performance and low computational complexity in PBR detection scene.

GS-orthogonalization OMP method for space target detection via bistatic space-based radar

A space-based bistatic radar system composed of two space-based radars as the transmitter and the receiver respectively has a wider surveillance region and a better early warning capability for high-speed targets, and it can detect focused space targets more flexibly than the monostatic radar system or the ground-based radar system. However, the target echo signal is more difficult to process due to the high-speed motion of both space-based radars and space targets. To be specific, it will encounter the problems of Range Cell Migration (RCM) and Doppler Frequency Migration (DFM), which degrade the long-time coherent integration performance for target detection and localization inevitably. To solve this problem, a novel target detection method based on an improved Gram Schmidt (GS)-orthogonalization Orthogonal Matching Pursuit (OMP) algorithm is proposed in this paper. First, the echo model for bistatic space-based radar is constructed and the conditions for RCM and DFM are analyzed. Then, the proposed GS-orthogonalization OMP method is applied to estimate the equivalent motion parameters of space targets. Thereafter, the RCM and DFM are corrected by the compensation function correlated with the estimated motion parameters. Finally, coherent integration can be achieved by performing the Fast Fourier Transform (FFT) operation along the slow time direction on compensated echo signal. Numerical simulations and real raw data results validate that the proposed GS-orthogonalization OMP algorithm achieves better motion parameter estimation performance and higher detection probability for space targets detection.

Range-Ambiguous Clutter Suppression with Cascaded FDA-MIMO STAP for Bistatic Space-Based Early Warning Radar

Range-Ambiguous Clutter Suppression with Cascaded FDA-MIMO STAP for Bistatic Space-Based Early Warning Radar

GNSS-Based Phase Synchronization for Bistatic and Multistatic Synthetic Aperture Radar

GNSS-Based Phase Synchronization for Bistatic and Multistatic Synthetic Aperture Radar

A Bistatic MIMO Radar System Exploiting Mixed-Resolution Quantization

A Bistatic MIMO Radar System Exploiting Mixed-Resolution Quantization

Multistatic radar distribution geometry effects on parameter estimation accuracy

AbstractAn analysis of the parameter estimation uncertainty for the target location and velocity achievable using a single‐transmitter‐multiple‐receiver multistatic radar system is presented. A framework for establishing measures of multistatic radar parameter uncertainties by expansion of the bistatic radar parameter uncertainty measures is presented for systems containing omnidirectionally radiating nodes. The methodology uses analytical methods based on the Cramér–Rao Lower Bounds applied to scenarios in a two‐dimensional physical space with a single target exhibiting Doppler characteristics and a bistatic angle dependent radar cross‐section. A set of geometric descriptors is proposed to characterise the system, and parameter uncertainty results are reported as a function of these descriptors. The results indicate that angular separation between the transmitter and the centre of the receiver distribution is of greater importance than the quantity of receivers within the system when low uncertainty estimation capabilities are desired, though a minimum of two receivers must be available. The proportion of receivers within the system which contributed information crucial to obtaining the minimum estimation uncertainty is reported for systems containing different quantities of receivers. It was observed that, as the total number of receivers available increased, the proportion of receivers required to achieve the minimal uncertainty level reduces significantly.

Doppler Ambiguity Compensation within the Batch for Weak Moving Target Detection in Passive Bistatic Radar

Doppler Ambiguity Compensation within the Batch for Weak Moving Target Detection in Passive Bistatic Radar

Clutter Characteristics Analysis and Range-Dependence Compensation for Space–Air Bistatic Radar

Clutter Characteristics Analysis and Range-Dependence Compensation for Space–Air Bistatic Radar

Polarimetric Analysis of Biseasonal Monostatic and Bistatic Radar Observations of a Glacier Accumulation Zone at Ku-Band

Polarimetric Analysis of Biseasonal Monostatic and Bistatic Radar Observations of a Glacier Accumulation Zone at Ku-Band

Clutter Cancellation in Passive Bistatic Radar With Transmitter Nonlinearity

Clutter Cancellation in Passive Bistatic Radar With Transmitter Nonlinearity

An Extensive Cancellation Algorithm Via Overlapping Subband for Time-Varying Clutter Suppression in Passive Bistatic Radar

An Extensive Cancellation Algorithm Via Overlapping Subband for Time-Varying Clutter Suppression in Passive Bistatic Radar

Multi-Frequency Coherent Integration Target Detection Algorithm for Passive Bistatic Radar

Multi-Frequency Coherent Integration Target Detection Algorithm for Passive Bistatic Radar

An LFM-Based Semiblind Synchronization Method for Bistatic Radar Imaging

An LFM-Based Semiblind Synchronization Method for Bistatic Radar Imaging