This paper deals with the problem of detecting a collision target in ground clutter, using a long integration time. A single reception channel being available, classical space time adaptive processing (STAP) cannot be used. After range processing, ground clutter can be modeled as a known interference subspace in the Doppler domain depending on its radial and orthoradial speeds. We exploit this a priori knowledge to perform an adpative detection of a collision target supposed to lie in a known and different subspace. A GLRT detector is first derived for known clutter covariance matrix. Then, the unknown covariance matrix is adaptively estimated from the projection of the data onto the modeled clutter subspace, and is plugged in the GLRT to form a suboptimal detector. The proposed scheme can be viewed as a synthetic STAP, for which the space domain is replaced by a clutter orthoradial information and longer integration time.

Waveforms transmitted by the elements of a MIMO radar system may differ in power and bandwidth. This raises the question of optimal resource allocation among the radar elements. Specifically, we are asking, given constrained resources, what is the optimal bandwidth and optimal joint power and bandwidth allocation for best target localization performance. Using the Cramér-Rao Lower Bound (CRLB) as the figure of merit for localization accuracy, the resource allocation optimization problem turns out to be non-convex. We apply a Difference of Convex functions programming approach to develop quasi-optimal algorithms for solving the resource allocation problems. A lower bound is also developed to help assess the quality of our solutions. Numerical examples demonstrate that bandwidth allocation has considerably more impact on performance than power allocation, and that the best performance is obtained with joint power and bandwidth allocation.

This paper proposes an improvement of the random multiple access scheme for satellite communication named Multislot coded ALOHA (MuSCA). MuSCA is a generalization of Contention Resolution Diversity Slotted ALOHA (CRDSA). In this scheme, each user transmits several parts of a single codeword of an error correcting code instead of sending replicas. At the receiver level, the decoder collects all these parts and includes them in the decoding process even if they are interfered. In this paper, we show that a high throughput can be obtained by selecting variable code rates and user degrees according to a probability distribution. With an optimal irregular degree distribution, our system achieves a normalized throughput up to 1:43, resulting in a significant gain compared to CRDSA and MuSCA. The spectral efficiency and the implementation issues of the scheme are also analyzed.

This paper addresses the problem of error correction of AIS messages by using the a priori knowledge of some information in the messages. Indeed, the AIS recommendation sets a unique value or a range of values for certain fields in the messages. Moreover, the physics can limit the range of fields, such as the speed of the vessel or its position (given the position of the receiver). The repetition of the messages gives also some information. Indeed, the evolution of the ship position is limited between messages and the ship ID is known. The constrained demodulation algorithm presented in this article is an evolution of the constrained Viterbi algorithm (C-VA). It is based on a modified Viterbi algorithm that allows the constraints to be considered in order to correct transmission errors by using some new registers in the state variables. The constraints can be either a single value or a range of values for the message fields. Simulation results illustrate the algorithm performance in terms of bit error rate and packet error rate. The performance of the proposed algorithm is 2 dB better than that obtained with the receiver without constraints.

The concept of delay/Doppler radar altimeter has been under study since the mid 90’s, aiming at reducing the measurement noise and increasing the along-track resolution in comparison with the conventional pulse limited altimeters. This paper introduces an analytical model of the mean backscattered power waveform acquired by a radar altimeter operating in SAR mode, as well as an associated least squares estimation algorithm. As for conventional altimetry, the mean power can be expressed as the convolution of three terms: the flat sea surface response, the sea wave height probability density function and the time/frequency impulse response of the radar. An important contribution of our work has been to derive an analytical formula for the flat sea surface response associated with Doppler altimetry. The double convolution defining the mean power can then be computed numerically. The resulting single-look model depends on three parameters: the epoch, the sea surface wave height and the amplitude. A multi-look model is obtained by summing all the reflected power from the along track beam surface of interest after applying appropriate delay compensation. The second contribution of our work concerns the estimation of the parameters associated with the single and multi-look analytical Doppler models. A least squares approach is investigated by means of the Levenberg-Marquardt algorithm (which does not need computing the exact model derivatives). Simulations conducted on synthetic altimetric waveforms allow the performance of the proposed estimation algorithm to be appreciated. The proposed analytical model (and the associated estimation algorithm) are finally compared with other models developed by the Centre National d'Etudes Spatiales (CNES) and the company Collecte Localisation Satellites (CLS) both located in Toulouse, France. The analysis of a huge number of Cryosat waveforms shows an improvement in parameter estimation when compared to the conventional LRM mode altimeter. These results are very promising.

Since the rise of technologies using GNSS positioning systems, development of carrier phase tracking receiver for precise point positioning in hostile environments is becoming one of the most important challenges for future satellite navigation applications. Because phase locked loops (PLL) that track carrier phase suffer from cycle slips phenomenon, noise robustness of the formers has to be reinforced if one wants to use precise positioning techniques in the widest range of challenging environments. The purpose of this article is to propose a new PLL design using a phase unwrapping algorithm that effectively corrects cycle slips due to phase noise in low CN0. Unlike phase unwrapping algorithms using a threshold approach for cycle slips detection, the algorithm implemented in our PLL structure is based on a system of prediction and pre-compensation of the phase dynamic stress. In order to reduce the cycle slips and enforce noise robustness of phase tracking, this algorithm is adapted to tracking loops with the aim to propose two innovative PLL structures. A comparative study is performed to show the effectiveness of the two proposed structures in case of noisy environment. 47

Propagation of monochromatic electro-magnetic waves in free space results in a widening of the spectral line. On the contrary, propagation preserves monochromaticity in the case of acous-tic waves. In this case, the propagation can be modelled by a linear invariant filter leading to attenuations and phase changes. Due to the Beer-Lambert law, the associated transfer function is an exponential of power functions with frequency-dependent parameters. In recent papers, we have proved that the acoustic propagation time can be modelled as a random variable following a stable probability distribution. In this paper, we show that the same model can be applied to the propagation in coaxial cables.

Positioning and navigation by GNSS in urban context are always challenging tasks, because of signal propagation problems such as shadowing effects and multipath. When not enough GNSS signals are received in line-of-sight (LOS), classical approaches mitigating multipath effects become insufficient because there is not enough reliable information available. Consequently, positioning errors can be about tens of meters, especially in urban canyons. In this paper, we introduce a NSS positioning approach that uses constructively non-line-of-sight (NLOS) signals in order to have enough information to compute the user’s position. In this work, we use the SE-NAV software to predict the geometric paths of NLOS signals using a high realistic 3D model of the environment. More precisely, we propose a new version of the extended Kalman filter augmented by the information provided by SE-NAV, referred to as 3D AEKF, for GNSS navigation in NLOS context. In the proposed approach, the measurement model traditionally based on the trilateration equations is constructed from the received paths estimated by SENAV. The Jacobian of the measurement model is calculated through knowledge of the objects on which the reflections have occured. To use even less reliable measurements, we propose a robust version of the 3D AEKF. Simulations conducted in realistic scenarios allow the performance of the proposed method to be evaluated.

Increased sensitivity and reduced fast time to first fix (TTFF) are key performance indicators for GNSS receivers, which depend on the surrounding environment, receiver design and available aiding information. To reduce the effect of attenuations, dynamics and navigation data bits transition, the GNSS acquisition engines employ both coherent and post-coherent signal integration strategies, namely non-coherent and differentially coherent. Understanding the advantages and drawbacks of each post-coherent integration strategy is fundamental in the process of optimization of the acquisition scheme, as well as the effect of high-dynamics in both coherent and post-coherent operations. In this paper, we study three important issues of GNSS acquisition. First, we propose a closed form expression to quantify the effect of a linearly changing Doppler frequency on the coherent integration output. Second, we derive a formula capable of characterizing the sensitivity gain of a differential integration detector. Third, we compare the effect of dynamics on both non-coherent and differential integration. The main objective of this work is to combine these three contributions for overall optimization of the acquisition scheme. More precisely, we mitigate the effect of large Doppler errors without compromising receiver’s sensitivity and ideally without additional computational cost.