Radar polarimetry is an applied fundamental science field that is focused on understanding interaction processes between radar waves and targets and disclosing their mechanisms. Radar polarimetry has significant application prospects in the fields of microwave remote sensing, earth observation, meteorological measurement, battlefield reconnaissance, anti-interference, target recognition, and so on. This study briefly reviews the development history of radar polarization theory and technology. Next, the state of the art of several key technologies within radar polarimetry, including the precise acquisition of radar polarization information, polarization-sensitive array signal processing, target polarization characteristics, polarization antiinterference, and target polarization classification and recognition, is summarized. Finally, the future developments of radar polarization technology are considered.

Polarization hierarchy and system operating architecture is one of the key technologies for Polarimetric Synthetic Aperture Radar (PolSAR) system design. In this paper the polarization hierarchies of PolSAR, including Single-Polarization radar, Dual-Polarization radar, Full-Polarization radar, and Compact Polarization radar, are discussed. In addition, the system operating architectures such as Polarization Timedivision multiplexing pulse, Polarization Frequency-division multiplexing pulse, Polarization Code-division multiplexing pulse and Polarization Space-division in Azimuth are presented more in detail.

The study on radar polarization information acquisition and processing has currently been one important part of radar techniques. The development of the polarization theory is simply reviewed firstly. Subsequently, some key techniques which include polarization measurement, polarization anti-jamming, polarization recognition, imaging and parameters inversion using radar polarimetry are emphatically analyzed in this paper. The basic theories, the present states and the development trends of these key techniques are presented and some meaningful conclusions are derived.

Multipath jamming is an effective self-defense jamming mode used to counter airborne fire-control radar or radar seekers. Multipath jamming has a deceptive jamming effect on the range, velocity, and angle of radar, making it difficult to identify and suppress. In this study, a polarized radar seeker structure is proposed. Based on the mechanism of the multipath jamming effect on radar, orthogonal polarization signal models of jamming and direct arrived signal are established. Next, a method to detect multipath jamming based on statistical property differences of polarization phases is proposed. The physical connotation of this method is clear and easy to realize. This method can be used to determine the presence of a jamming signal and identify the signal pattern and polarization types. The feasibility of this method has been verified via a simulation experiment, thereby demonstrating that the method serves as a useful reference for effectively countering multipath jamming.

Radar detection and tracking performance in the UHF-band can be influenced by the downlink signals of communication base stations. The polarimetric properties of interference from base stations are measured and analyzed as a basis for suppressing this type of interference by a polarization processing method. In this study, we establish signal models from the base station for dual-polarization UHF-band radar. We express the Probability Density Functions (PDF) of the estimated polarization ratio and degree of polarization in a closed form and use them to describe the statistical properties of the interference environment. We developed polarimetric radar reception experiments for the signals from both Single-Base Stations (SBS) and Multi-Base Stations (MBS). Experimental results proved that deterministic polarized descriptions are appropriate only for signals from SBS but not from MBS or from stations with a low DoP (Degree of Polarization). However, the proposed statistical method can be used to describe both SBS and MBS cases, which we demonstrated by comparing the theoretical models with real measurement data.

In this paper, we analyze the space polarization and frequency dispersion characteristics of the polarimetric High Resolution Range Profile (HRRP) of manmade targets. We integrate these characteristics and propose a novel scheme for scattering mechanism identification. Using a polarization decomposition technique, the scheme first identifies the scattering mechanism of the scattering centers. Specially, it uses an algorithm to compensate for the polarization orientation angle in order to decrease the errors in judgment caused by the varying azimuth. Then, based on the frequency dispersion characteristics, we design threedimensional parameters to discriminate between the scattering centers, in order to decrease the inaccuracy in the discriminations. Finally, we conduct simulations based on electromagnetic data to validate the feasibility of the proposed scheme and to demonstrate that it provides a basis for practical use in target recognition.

This study is based on the application requirements of fully polarimetric radar for aircraft detection and target recognition. We focus on fully polarimetric scattering characteristics of air targets, particularly the cross-polarimetric scattering mechanism and its availability. In the ultra-high frequency band, we conduct numerical modeling and simulation of stealth and non-stealth aircraft targets. The spatial distribution characteristics of polarimetric scattering for different aircraft targets are studied and compared, and the structures that could cause strong cross polarization are analyzed. The results of this study suggest that nonstealth aircraft have more polarimetric characteristics; this will help people use polarimetric radar for detecting aircraft.

Meteorological target simulation using polarization information is the foundation of the theoretical research and design application of dual-polarization Doppler weather radar. Currently, the theoretical research of airborne dual-polarization weather radar is in the development stage. To provide high-fidelity simulation data required for airborne dual-polarization weather radar detection technology, in this study, a simulation method of the polarization characteristics of rainfall determined using airborne weather radar based on numerical weather prediction is proposed. The numerical weather prediction model is used to realize the modeling and simulation of meteorological scenarios and provide information on meteorological parameters such as temperature, particle concentration, and mixing ratio of rainfall. In the analysis of the microphysical properties of rainfall, the electromagnetic scattering matrix is calculated and the simulation of the polarization characteristics of rainfall is achieved. The simulation results for different microphysical property parameters have led to the establishment of a high-fidelity rainfall model and demonstrated (via comparison with the real radar data) that the simulation of polarization characteristics using the proposed method is effective and reliable.

The polarization feature of a fully Polarimetric Phased-Array Radar (PPAR) antenna varies according to the beam-scanning angle, thereby introducing two problems on the target Polarization Scattering Matrix (PSM) measurement. First, the antenna polarization basis is defined within the vertical cross-section of an electromagnetic wave propagation direction, and the polarization basis of each beam direction angle is not identical, resulting in the PSM of a fixed-posture target observed by PPAR being not identical for different beam-scanning angles. Second, the cross polarization of the PPAR antenna increases with increasing beamscanning angle, resulting in a crosstalk among the elements of PSM observed by PPAR. This study focuses on the analysis of the abovementioned two aspects of the effect of beam scanning on target PSM observed by PPAR. The results will establish a more accurate observation of the equation for the precision PSM measurement of PPAR.

This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our method can efficiently represent polarimetric signatures of different land covers and yield satisfactory classification results.

Since classification methods based on H/α space have the drawback of yielding poor classification results for terrains with similar scattering features, in this study, we propose a polarimetric Synthetic Aperture Radar (SAR) image classification method based on eigenvalues. First, we extract eigenvalues and fit their distribution with an adaptive Gaussian mixture model. Then, using the naive Bayesian classifier, we obtain preliminary classification results. The distribution of eigenvalues in two kinds of terrains may be similar, leading to incorrect classification in the preliminary step. So, we calculate the similarity of every terrain pair, and add them to the similarity table if their similarity is greater than a given threshold. We then apply the Wishart distance-based KNN classifier to these similar pairs to obtain further classification results. We used the proposed method on both airborne and spaceborne SAR datasets, and the results show that our method can overcome the shortcoming of the H/α-based unsupervised classification method for eigenvalues usage, and produces comparable results with the Support Vector Machine (SVM)-based classification method.