The azimuth multichannel synthetic aperture radar (SAR), as one of the mainstream technologies for achieving high-resolution and wide-swath (HRWS) imaging, has been successfully employed in several on-orbit SAR missions. However, the unavoidable phase errors among channels result in azimuth ambiguity, deteriorating the recognizability of targets in SAR images. Additionally, the radio frequency interference (RFI) exacerbates the difficulty of phase error estimation. To address this issue, a phase error calibration method based on least spectrum difference (LSD) is proposed. Firstly, the multichannel signals are reconstructed using the linear mapping form of the reconstruction algorithm. Secondly, the objective function is established based on the continuity of the azimuth spectrum, by which only the signals near the discontinuity points are proposed. Finally, the optimal estimation of the phase differences can be obtained after iteration. In LSD method, the RFI to the objective function is mitigated due to the operation in the range-Doppler domain, and the iteration is proposed only using a few data near the discontinuity points thus saving much computational cost. Experimental results based on the simulated data and real bistatic echoes of the LuTan-1 (LT-1) mission validate the superiority of the proposed LSD method.

Range ambiguity is a technical challenge due to the deterioration of the image quality in the multistatic synthetic aperture radar (SAR) constellations. This article proposes an effective range ambiguity suppression scheme based on multiechoes coherent processing. First, a general signal model impacted by range ambiguity is built up based on the geometry of the multistatic SAR constellation, showing the different phase characteristics of the desired and ambiguous signals between the satellites. Then, an effective processing scheme for range ambiguity suppression is proposed based on the different phase characteristics, and the corresponding ambiguity suppression performance (ASP) is analyzed accordingly. This scheme can achieve a coherent summation of the desired signals by compensating for the corresponding phase difference, while the ambiguous signals are summed incoherently. Therefore, the range ambiguities can be suppressed without increasing the SAR instrument complexity. Finally, the system and imaging simulation results are provided to validate the theoretical analysis of the ASP and demonstrate the effectiveness of the proposed scheme, respectively.

With the growing scarcity of spectrum resources, frequency sharing among different systems is becoming quite common, which causes radio frequency interference (RFI) to normal SAR applications. Recently, in the RFI suppression field, algorithms based on the low-rank property (LRP) assumption have become a popular research topic. However, this assumption is not valid in complicated cases, especially when there is a wide variety of RFIs. To address this problem, in this paper, factors that affect the LRP are studied through theoretical analysis and simulation verification, a general RFI model is established to fit complicated cases, and an advanced RFI suppression scheme based on low-rank property restoration (LRPR) is proposed. The LRPR scheme has three steps. The first step is RFI localization, which captures the rough profile of the RFI in the time-frequency domain for RFI spectrum separation and extraction. The second step is RFI clustering, in which a novel similarity evaluation metric and corresponding two-step clustering algorithm are designed. The final step is RFI suppression. Operations for LRP recovery in each RFI group are proposed, consequently, classical low-rank approximation methods are applied for RFI suppression. The simulation results for various types of RFI show the robustness and performance improvement of the proposed scheme. In addition, in LuTan-1 data processing, the proposed scheme outperforms classical algorithms in both intensity image recovery and phase preservation.

Frequency scanning (F-SCAN) synthetic aperture radar (SAR), as an advantageous choice for SAR systems operating at higher carrier frequencies, can achieve high performance in terms of swath width, azimuth resolution, and signal-to-noise ratio (SNR). In this article, a novel nonlinear F-SCAN (NF-SCAN) SAR imaging mode is proposed. Compared to the F-SCAN SAR, NF-SCAN SAR has two main advantages: one is to change the distribution of the transmit bandwidth over the swath by precisely tuning the beam scanning response to frequency. The other is to adapt the SNR distribution by adjusting the beam scanning response to time. First, this article derives the system parameters for NF-SCAN SAR. Second, methods for designing nonlinear beam scanning responses (NBSRs) to frequency and time (NBSR-F and NBSR-T) are proposed, by which a well-balanced ground range resolution and adaptive SNR are acquired. Third, a waveform design method dedicated to NF-SCAN SAR is given and the corresponding signal model is derived in detail. To reduce the data rate of NF-SCAN SAR with an incompletely compressed echo window, an improved data subsampling algorithm (IDSSA) is proposed, where a precise filter is designed, thus avoiding the loss of effective bandwidth. Finally, simulation experiments are conducted to verify the superiority of NF-SCAN SAR imaging mode. The proposed NF-SCAN SAR can be viewed as an important candidate for high-performance spaceborne SAR.

This paper proposes an advanced radio frequency interference (RFI) mitigation scheme for the phase synchronization of the bistatic SAR (BiSAR) system based on the blind source separation (BSS) technique, by which narrowband and wideband RFI can be suppressed significantly. First, the RFI signal model is built up and the impact of the RFI on the phase synchronization is analyzed accordingly. Second, a phase synchronization system with multiple receiving channels and the corresponding blind identification diversity (BID) method are proposed to separate the synchronization signal from the contaminated data with less signal loss. In BID, a novel peak detection algorithm is presented to solve the inherent ambiguity of the BSS. Finally, the simulation and experimental results based on the BiSAR system LuTan-1 are presented to validate the advantages of the proposed scheme.

A novel noncoherent microwave imaging principle with periodical or random radio frequency (RF) illumination is proposed in this article. Implemented with circular array synthetic aperture radar (SAR) frontend and low-complexity signal processing algorithms, the imaging device, called RF camera, achieves some desired properties similar to an optical camera, such as the capability to operate with multiple uncoordinated illuminators. Different from conventional multistatic imaging, the RF camera does not require any knowledge about an illuminator’s location or signal waveform. A static illumination sensor (IS) can be used to provide a reference signal for image reconstruction. With periodical illumination, the RF camera can even operate without IS, but the imaging performance can be improved with IS. With random illumination, the IS is necessary for the RF camera operation, and the imaging distortion can be described by a point blur function. Theoretical analyses on the imaging signal-to-noise ratios are performed under different RF camera operation modes. Simulation and experimental tests are conducted using 77-GHz millimeter wave frequency to verify the noncoherent imaging principle and its performance.

This article presents an universal circular synthetic aperture radar (SAR) (UCSAR) by which the targets to be observed at any radial distance can be imaged, thus making SAR imaging possible in a more general scenario with a circular movement of the radar platform. The UCSAR point spread function (PSF) is firstly analyzed based on the time-domain correlation imaging approach, and thus a three-dimension (3-D) spatial variant PSF of the target can be formulated. The closed-form PSF expressions with single-frequency and frequency-modulated continuous wave (FMCW) transmitted signals are derived respectively to quantify the imaging resolutions, showing that the PSF is a product of a sinc function and a zeroth-order Bessel function when using a wideband FMCW signal. Secondly, a fast UCSAR imaging algorithm and its further simplified version are proposed to reduce the computational cost significantly based on the piecewise constant Doppler (PCD) principle. To quantify the imaging performance, we derive an error function of the slant range approximation for the proposed algorithm, serving as a practical guideline for the UCSAR parameter selection. Finally, the simulation and experimental results are provided to validate the PSF analysis, the fast imaging algorithm, and the implementation of the proposed UCSAR.

This paper proposes a new synthetic aperture radar (SAR), named as panoramic SAR, based on a combination of linear and rotational SARs, by which a large 360-degree panoramic view of the observed scene can be reconstructed. Firstly, the system geometry and its imaging process based on the back-projection algorithm (BPA) are presented. The combined movement constitutes a two-dimensional synthetic aperture and thus higher imaging resolutions can be obtained. The corresponding resolution analysis and the sampling criteria are discussed accordingly. Then, a novel dynamic piecewise compensation (DPC) algorithm, a recursive imaging process, is proposed to reduce the processing complexity significantly. The imaging implementation and the complexity are also studied respectively. Finally, a prototype of panoramic SAR is built based on an frequency modulated continuous wave (FMCW) radar and a moving platform, and the simulation and experimental results are provided to validate the proposed panoramic SAR principle and the DPC algorithm.

A novel 3-D time-domain terahertz (THz) imaging system based on piecewise constant Doppler (PCD) algorithm and step-frequency continuous-wave (SFCW) signaling is proposed in this article. First, the SFCW THz imaging system configuration and the Gaussian beam propagation model are introduced. Then, the conventional time-domain correlation imaging algorithm is reviewed, and the closed-form expression of its point spread function (PSF) is derived to quantify the range and lateral resolutions. To reduce the computational complexity, a 2-D recursive imaging process based on the plane approximation of the range surface is proposed, by which the original PCD algorithm is extended for 3-D imaging with 2-D aperture synthesis. The 3-D PCD imaging principle, implementation, and complexity analysis are discussed afterward. Finally, simulation and experimental results are provided to validate the theoretical analysis of the 3-D time-domain THz imaging and demonstrate the high quality of the proposed imaging algorithm at a low computational cost.

A novel generalized continuous-wave synthetic aperture radar (GCW-SAR) based on deramp-on-receive operating in millimeter-wave frequency is proposed in this article. With deramp-on-receive, the receiver sampling rate is drastically reduced, and the downsampled 1-D raw data can be obtained from the received beat signal. Further adopting piecewise constant Doppler (PCD) imaging in the digital domain, a GCW-SAR image can be easily reconstructed by using the existing frequency-modulated continuous-wave (FMCW) radar system. The effects of deramp-on-receive in PCD imaging are analyzed accordingly. The short wavelength of the millimeter-wave carrier used in the proposed GCW-SAR enables high azimuth resolution as well as a short synthetic aperture, which, in turn, significantly reduces the imaging computational complexity. Simulation and experimental results confirm the advantages of the proposed GCW-SAR.

Generalized continuous wave synthetic aperture radar (GCW-SAR) is a promising new imaging radar system since it applies the full-duplex (FD) transmission technique to achieve continuous signaling in order to overcome several fundamental limitations of the conventional pulsed SARs. As in any FD wireless communication system, self-interference (SI) is also a key problem which can impact on the GCW-SAR system. In this paper, the analog least mean square (ALMS) loop in the radio frequency domain is adopted to cancel the SI for a GCW-SAR system with periodic chirp signaling. The average residual SI power after the ALMS loop is analyzed theoretically by a stationary analysis. It is found that the ALMS loop not only works with random signals in general FD communication systems, but also works well with the periodic signal in GCW-SAR systems. Simulation results show that over 45 dB SI cancellation can be achieved by the ALMS loop which ensures the proper operation of the GCW-SAR system.

A generalized continuous wave synthetic aperture radar (GCW-SAR) concept is proposed in this paper. By using full-duplex radio frontend and continuous wave signaling, the GCW-SAR system can overcome a number of limitations inherent within the existing SAR systems and achieve high-resolution and wide-swath remote sensing with low-power signal transmission. Unlike the conventional pulsed SAR and the frequency-modulated continuous-wave SAR, the GCW-SAR reconstructs a radar image by directly correlating the received 1-D raw data after self-interference cancellation with predetermined location-dependent reference signals. A fast imaging algorithm, called the piecewise constant Doppler (PCD) algorithm, is also proposed, which produces the radar image recursively in the azimuth direction without any intermediate step, such as range compression and migration compensation, as required by conventional algorithms. By removing the stop-and-go assumption or slow-time sampling in azimuth, the PCD algorithm not only achieves better imaging quality but also allows for more flexible waveform and system designs. Analyses and simulations show that the GCW-SAR tolerates significant self-interference and works well with a large selection of various system parameters. The work presented in this paper establishes a solid theoretical foundation for next-generation imaging radars.

Attention has been devoted to Synthetic Aperture Radar (SAR) for half a century. Though it is a well-proven remote sensing technique, conventional pulsed SAR has several inherent limitations. In this paper, we present a new SAR concept, called Generalized Continuous Wave SAR (GCW-SAR). By using continuous wave signaling, the GCW-SAR system achieves better performance and overcomes the limitations such as the minimum antenna area in conventional SAR. Unlike the frequency modulated continuous wave SAR (FMCW-SAR) system, the GCW-SAR image is reconstructed by correlation between the sampled raw data and the location dependent reference signals. A fast image reconstruction algorithm is also presented in the paper. The principle of GCW-SAR and the effectiveness of the proposed algorithm are validated by numerical simulation results.

In this paper, a new detection framework, namely, deep sensing (DS), is proposed for 5G spectrum sharing, which is designed to proactively recover some informative states associated with realistic cognitive links (e.g., fading gains), except for detecting the occupancy of primary-band. Relying on a dynamic state-space approach, a unified mathematical model is formulated. The Bernoulli random finite set (BRFS) is exploited to theoretically characterize the complex DS procedures. A Bernoulli filter algorithm is suggested to recursively estimate unknown PU states accompanying related link information, which is further implemented by particle filtering. The proposed DS algorithm is applied to detect primary users over more challenging time-varying fading channels. Numerical simulations validate the new scheme. Spectrum sensing can be effectively implemented by estimating time-varying fading gains jointly.

Spectrum sensing, as one of the most important aspects, plays a crucial role on mitigating interference of secondary users (SU) in cognitive radio. However, moving primary user (PU) will sharply decrease the stability of observable information by considerably deteriorating the sensing performance. In this paper, a new joint estimating scheme is proposed for tracking PU proactively and detecting the occupation of primary band meanwhile. In view of both PU's state and its location, the united mathematical model based dynamic state-space model (DSM) is established in the new scheme. On this basis, a Bernoulli filter algorithm is suggested to jointly estimate the PU's state and its location recursively, which is further implemented by Particle filtering. Furthermore, an adaptive horizon expanding method is subtly designed to deal with loss of tracking resulting from the intermittent disappearance of PU's state. Experimental simulations demonstrate that, aiming at mobile PU, sensing performance of the new scheme is apparently better than other traditional methods, and the estimated PU's location may be further utilized by resource allocation of cognitive network.

In this paper, spectrum sensing is investigated and a new detection framework, namely, deep sensing (DS), is proposed for more challenging scenarios of future dynamic spectrum sharing. In contrast to existing methods, the DS scheme is designed to proactively recover and exploit some other informative states associated with realistic cognitive links (e.g., fading gains), except detecting the occupancy of primary-band. A unified mathematical model, relying on the dynamic state-space approach, is formulated, in which the Bernoulli random finite set (RFS) is further exploited to theoretically characterize complex DS procedures. A Bernoulli filter algorithm is suggested to recursively estimate unknown PU states accompanying related link information, which is implemented by particle filtering based on numerical approximations. The proposed DS algorithm is applied to detect primary users under time-varying fading channel, which may increase the observation uncertainty and, therefore, deteriorate the sensing performance. With this new framework, the time-varying fading gain, modeled as a stochastic discrete-state Markov chain (DSMC), is estimated along with unknown PU states. Simulations demonstrate that, by exploiting the underlying dynamic fading property, the sensing performance will surpass other traditional schemes. The DS scheme may be conveniently generalized to other applications, which will promote sensing performance and provides a new paradigm for next-generation spectrum sharing.