Spaceborne global navigation satellite system reflectometry (GNSS-R) techniques have been developed for sea surface wind speed retrieval in recent years. In order to utilize both the leading edge slope (LES) and normalized bistatic radar cross-section (NBRCS), the minimum variance estimator (MVE) is used in the cyclone GNSS (CYGNSS) algorithm for wind retrieval. However, due to the high correlation of two observables, the root mean square error (RMSE) of the MVE estimated winds is not improved significantly. In this article, a new method by combining retrievals from delay-Doppler map (DDM) observables based on particle swarm optimization (PSO) is proposed. LES and NBRCS observables from CYGNSS V2.1 products are used, and then wind retrievals from them are combined by PSO. In order to validate the performance, European Center for Medium-Range Weather Forecasts (ECMWF) and cross-calibrated multi-platform (CCMP) ocean surface wind vector analysis product 10-m ocean surface wind products are used as ground truth. The results show that, when using ECMWF winds, the RMSE of MVE retrievals is 2.21 m/s, while that of PSO is 1.95 m/s: an improvement of 12%; when using CCMP winds, the RMSE of MVE retrievals is 2.15 m/s, while that of PSO is 1.92 m/s: an improvement of 11%. Therefore, we conclude that the PSO algorithm is an improvement on the state-of-the-art MVE GNSS-R-based wind speed retrieval techniques. However, the PSO-based wind retrievals show the dependence on the GPS block type and the CYGNSS satellite identifier that the MVE-based techniques suffer from.

The motion of any potential sea-targets in a sequence of delay Doppler maps (DDMs) collected by a spaceborne global navigation satellite system-reflectometry (GNSS-R) receiver can be computed as a priori information due to the receiver velocity dominating that of any realistic sea-targets. This can be exploited to design a matched filter to detect sea-targets in a DDM sequence without the requirement for any (pre)detection and can be considered a track-before-detect technique. In this article, such a filter is developed and applied to DDMs collected by TechDemoSat-1, and the detection of sea-ice is demonstrated. A frequency analysis of simulated and actual DDM sequences containing a sea-target is carried out. We show that the stationary sea-clutter is bound to the zero time-frequency plane in the 3-D frequency response of the DDM time series, while only ≈13.8% of the target's energy is located in this plane. This finding motivates the application of an adaptive whitening filter to blindly suppress the temporally correlated clutter in the DDM sequence before applying the matched filter to the prewhitened sequence containing a spatially fixed point-like response arising from the edge of an ice sheet, which is equivalent to a point-like sea-target such as a ship. This results in a signal-to-clutter ratio of ≈12 dB being achieved when processing only the weak target responses at nonspecular locations originating from the spatially fixed edge of the ice sheet. This is the first technique to exploit the delay and Doppler dynamics of a target to obtain a coherent integration gain.

Accurate determination of the specular point is important for simulating and processing reflected global navigation satellite system signals for remote sensing applications. Existing methods for determining the specular point are based on both spherical and ellipsoidal approximations of the Earth and employ either Snell’s law or Fermat’s principle to formulate the problem. By analysis and simulation, it is shown that these methods produce significant errors at intermediate latitudes. In this paper, a novel formulation for the solution of the specular point is proposed that satisfies Snell’s Law on the WGS84 ellipsoid. The proposed method is compared with the existing methods for various receiver orbit configurations and algorithm augmentations. It is shown that the proposed method is more accurate than the existing methods and more computationally efficient than the minimum path length (MPL) method. Additionally, the resultant grazing angles, MPL method errors, and specular point locations as a function of the receiver orbit are investigated, leading to the finding that the likelihood of an error is significant for geometries favored by reflectometry applications.

It has been demonstrated that delay-Doppler (DD) maps (DDMs) retrieved from spaceborne Global Navigation Satellite Systems Reflectometry missions contain sea clutter and also potential sea targets. Examples of sea targets include sea ice, oil rigs, and oil slicks. To distinguish sea targets from sea clutter, one can estimate the sea clutter and subtract it from the DDM, leaving behind only the sea target’s signature on the DDM. This is computationally expensive and will not be robust when the sea clutter estimate is poor or if there are DD tracking errors. This article presents two blind methods for the suppression of sea clutter: first, an adaptive filter and second, an infinite impulse response low-pass filter. We use real DDMs collected by TechDemoSat-1 to show the autoregressive, hence temporally correlated nature of the DDM time series, and present evidence that two blind methods can suppress clutter at least as effectively as the existing method, albeit at a fraction of its computational cost.