Spaceborne multichannel (MC) synthetic aperture radar (SAR) can achieve high-resolution and wide-swath (HRWS) imaging. However, for an MC SAR system that does not satisfy the displaced phase center antenna (DPCA) condition, ghosts will appear in the image when the traditional back projection (BP) algorithm based on direct coherent integration is applied. To obtain the image without ghosts, an MC-BP algorithm based on time-domain channel weighting is proposed in this article. Compared with the traditional BP algorithm for single-channel signal, this algorithm just adds a channel-weighting factor in coherent integration. The channel-weighting factor is determined based on the channel index and ambiguity index, which is selected based on the instantaneous space angle of the pixel. Different from the existing MC imaging methods including two steps: signal reconstruction and imaging, the proposed method fulfills the image formation in one step and thus is simpler. Moreover, it can adapt the process of MC and multimode [stripmap, spotlight, sliding spotlight, and terrain observation by progressive scans (TOPSs)] data without any extra operation. To improve the efficiency of the MC-BP algorithm and overcome the defocusing issue caused by the Earth’s curved surface in the spaceborne geometry, a fast MC-BP algorithm based on a local spherical coordinate system, i.e., MC spherical Cartesian fast BP (MC-SCFBP) algorithm, is further developed. The spaceborne SAR simulation results with 0.1-m resolution are given to verify the effectiveness of this algorithm.

The Doppler dispersion of the received signal is very severe when the beam width of the antenna is wide, resulting in a decrease in localization accuracy for Multiple Radiation Source Localization. To resolve the problem, we propose a passive signal focusing algorithm (PSFA) for multiple radiation sources localization based on a full aperture model. The full-aperture model overcomes the resolution degradation in conventional sub-aperture processing. In the PSFA, the residual frequency correction (RFC) eliminates the localization bias in the azimuth domain and the instantaneous Doppler compensation (IDC) resolves the Doppler dispersion in the range domain, improving localization accuracy. The matched filtering is used to complete precise azimuthal focusing and the locations are obtained according to the focusing results. Moreover, the Cramer-Rao lower bound (CRLB) for synthetic aperture localization is derived. The CRLB is essential for evaluating algorithms in theoretical studies and designing system parameters in practical applications. Finally, The CRLB, simulation, and acquired data are used to evaluate the localization performance.

In satellite synthetic aperture positioning (SAP), the curvature of the Earth’s surface and the curved orbit lead to nonlinear and asymmetric instantaneous Doppler frequencies, especially when dealing with signals of very long durations. This phenomenon significantly affects the accuracy of center frequency estimation and radiating source positioning. This study presents an ultra-high-resolution positioning algorithm designed to process ultra-long-duration data collected by a single satellite. Initially, a method for estimating the zero-Doppler moment based on sub-aperture chirp rates is proposed to obtain an unbiased estimate of the radiation source’s center frequency. Subsequently, a nonlinear instantaneous Doppler compensation method is proposed, utilizing the estimated center frequency and chirp rates to enhance the coherence of the long-duration data. Furthermore, a long coherent positioning is suggested to generate an ultra-high-resolution positioning image. Ultimately, the efficacy of the proposed algorithm is validated through simulations and acquired data.

With the rapid growth of the Internet of Things (IoT), fundamental security measures of wireless networks have become a basic requirement. Aiming at the identification of wireless transmitters with the same parameters, this paper proposes a specific emitter identification (SEI) method based on time-frequency feature extraction. Received signals go through preprocessing, i.e., multipath effect estimation and Doppler frequency compensation, to mitigate the channel effect. Then the time-frequency spectrum is generated and a time-frequency feature extraction network is constructed to achieve feature extraction and identification task. Real-world data are used to verify the effectiveness of the proposed method. The overall identification accuracy for stationary emitters reaches 92.9%. Besides, the proposed preprocessing method improves moving emitter identification accuracy by 12%.

The wavenumber domain algorithm is an ideal solution for high-resolution and highly squinted (HRHS) synthetic aperture radar (SAR) imaging in the case of an ideal straight trajectory. However, for airborne HRHS SAR imaging, the Stolt mapping leads to nonsystematic range cell migration (NsRCM) and secondary range compression (SRC) for the HRHS SAR, which causes the HRHS SAR image to defocus severely. To obtain a well-focused HRHS SAR image, a new autofocusing algorithm for HRHS SAR imagery based on an equivalent broadside model is proposed in this article. After coarse motion compensation, linear range walk correction and azimuth resampling are employed to transform the HRHS SAR data into the equivalent broadside SAR data, which has been proved to greatly reduce NsRCM and SRC. After that, the motion error prior structure in the 2-D wavenumber domain is revealed. According to the structure, a novel 2-D wavenumber domain autofocusing algorithm is proposed by the relationship between the 1-D azimuth phase error and the 2-D wavenumber domain phase error correction. Finally, the well-focused HRHS SAR imagery is obtained. Experiments based on simulated and acquired data are carried out to verify the necessity and effectiveness of the proposed algorithm for HRHS SAR imaging.

Frequency hopping (FH) signal is one of the research hotspots of passive positioning. Aiming at the problem of FH signal localization, this paper proposes a synthetic aperture passive positioning method. The method estimates and compensates for the baseband modulation of the received signal. Then the received signal vectors are arranged into a two-dimensional matrix. The Doppler frequency of each pulse is compensated by the Doppler frequency compensate matrix. The cost function is constructed by a two-dimensional focus of the received signal, and the emitter position is directly obtained through a gird search. Simulation and experimental data verify the effectiveness of the proposed method.

The nonlinear variation of viewing angles over a long duration causes a nonlinear initial phase of the received pulse in a passive positioning system with a single moving receiver. Typical positioning systems ignore the phase and perform incoherent accumulation of the long-time data, resulting in a decrease in positioning accuracy, especially at a low signal-to-noise ratio (SNR). A novel passive positioning system with a synthetic aperture technique, named synthetic aperture positioning (SAP) system, is proposed to resolve the issue. First, a new 2-dimensional (2-D) continuous sampling working model is proposed. Then, the SAP system and a cost function are given to analyze the positioning performance. Third, a positioning algorithm based on the maximum likelihood estimation (MLE) is studied to handle the cost function and position the emitter. Simulation and experimental results verify the validity and effectiveness of the proposed SAP system.

A long synthetic aperture passive localization method for two Frequency shift keying (2FSK) signal via azimuth chirp-rate contour is proposed in this paper. By introducing synthetic aperture radar (SAR) imaging technology into passive localization, Doppler frequency change rate of received signal, which is called as azimuth chirp-rate in this paper, is estimated by azimuth focusing. Then, a grid map is formed on the ground and azimuth chirp-rate of each point is calculated to get an azimuth chirp-rate contour map. In the contour map, signal emitter is located in an azimuth chirp-rate curve in which the azimuth chirp-rate value is equal to its estimate. The azimuth chirp-rate contour map of a ground area varies with position of sensor. Therefore, two different azimuth chirp-rate curves can be obtained through different periods of a trajectory and the intersection of the two curves gives estimate of the emitter location.

This paper presents a new method for estimating the baseline error of an azimuth multi-channel SAR antenna in the SAR image domain. In this paper, the expressions of the image domain of multi-channel SAR signals with azimuth baseline errors are derived. The covariance matrix of the image domain signals is obtained by using the joint pixel method. Finally, the least-squares method of image domain is deduced to estimate the azimuth baseline of multi-channel SAR error. Simulation experiments verify the effectiveness of the proposed method.