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, thus 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-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.

In passive localization, the received signal may come from multiple signal sources with different modulations. The modulations are usually resolved by high-order spectrum (HOS) processing. However, the processing causes multiple intersignal cross terms, resulting in a degradation of localization performance. To resolve the problem, this article proposes a CLEAN-based synthetic aperture passive positioning algorithm for multiple signal sources. The main idea is to locate the same modulated signal by focusing and then filtering out the located signal. Signals with the same modulation are located through the synthetic aperture passive localization method. Then, the located signals are removed and the remaining signals are recovered through inverse focusing. The multiple signals are focused, extracted, and separated according to the modulation. The effect of cross terms and multiplicative noise in the HOS is dramatically reduced. The simulation experiments show that the proposed algorithm can effectively improve localization accuracy.

The time difference of arrival (TDOA) and frequency difference of arrival (FDOA) between two receivers are widely used to locate an emitter. Algorithms based on cross ambiguity functions can simultaneously estimate the TDOA and FDOA accurately. However, the algorithms, including the joint processing of received data, require transferring a large volume of data to a central computing unit. It can be a heavy load for the data link, especially for a wideband signal obtained at a high sampling rate. Thus, we proposed a multi-pulse cross ambiguity function (MPCAF) to compress the data before transmitting and then estimate the TDOA and FDOA with the compressed data. The MPCAF consists of two components. First, the raw data are compressed with a proposed two-dimensional compression function. Two methods to construct a reference pulse used in the two-dimensional compression function are considered: a raw data-based method constructs the pulse directly from the received signal, and a signal parameter-based method constructs it through the parameters of the received signal. Second, a wideband cross-correlation function is studied to refine the TDOA and FDOA estimates with the compressed data. The simulation and Cramer–Rao lower bound (CRLB) analyses show that the proposed method dramatically reduces the data transmission load but estimate the TDOA and FDOA well. The hardware-in-the-loop simulation confirms the method’s effectiveness.

The wavenumber-domain algorithm is an ideal solution for high-resolution and highly-squinted (HRHS) 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 equivalent broadside model is proposed in this paper. 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.

The frequency hopping (FH) signal has received much research interest due to its low interception probability. In the FH signal localization, the variation of signal frequency introduces error into localization methods involving phase or frequency information. In order to deal with the problem of positioning measurement estimation for unknown FH signal emitters, this article proposes a synthetic aperture passive positioning method. Baseband modulation of received signals is compensated by the time difference method. Then, the de-chirp method is introduced for carrier frequency estimation. The Doppler frequency of each pulse is compensated by a Doppler frequency compensation matrix, and the cost function related to the emitter position is constructed by 2-D focus results of the received signal at all frequencies. The emitter position is obtained through a gird search. Simulation and experimental data show that the proposed method is superior to several existing positioning methods especially when the signal-to-noise ratio (SNR) is low.

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 ultrahigh-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 ultrahigh-resolution positioning image. Ultimately, the efficacy of the proposed algorithm is validated through simulations and acquired data.