Stéphane Kemkemian

Toward common radar & EW multifunction active arrays

Military Air platforms are fitted with Fire Control or Surveillance Radars, usually operating in X-band, Electronic Warfare Systems (EWS), and some radio links. Each of these systems is dedicated to a particular task and the cooperation is reduced to a minimal exchange of information between them mainly for avoiding mutual disturbances. Major system performance enhancements are to be expected thanks to close co-operations of one sensor to each others and thanks to the sharing of resources, especially in the field of multifunction AESA antenna sharing. The future co-operations can be ordered in four levels. The levels one to three lead progressively to a multi-functions sensor. The last one is the deployment, on a single or multiple platforms, of compact multi-functions sensors on a network basis. Another area of co-operation is the realization of R.F. functions such as “ad-hoc” communication functions using the Radar or the EWS multifunction R.F. and antennas.

Sense and avoid radar using Data Fusion with other sensors

UAV (Unmanned Aerial Vehicle) are employed in crisis or war times. For training purposes, they must be flown in special areas called “segregated areas”. In the future, both for emerging civilian applications and for training purposes, UAV will have to be inserted into the general Air traffic. So, UAV will have to be equipped with “Sense and Avoid” systems. An interesting solution is to merge a co-operative sensor like ADS-B and a non-cooperative “all weather” one, namely Radar. In favorable cases, the Radar measurements can be improved by using additional Electro-Optical sensors, for instance video sensors.

Radar and electronic warfare cooperation: How to improve the system efficiency

Up to now, combat aircrafts are fitted with Fire Control Radar (FCR), Electronic Warfare System (EWS), and some radio links. Each of these systems is dedicated to a particular task and the cooperation is reduced to a minimal exchange of information between them, so far. Major system performance enhancements are to be expected from close cooperations to each other sensors. The future co-operations can be ordered in four stages. The first three ones lead progressively to a multi-functions sensor. The last one is the deployment, on a given platform, of compact multi-functions sensors on a network basis. Another area of co-operation is the realization of R.F. functions that are currently provided by other devices using other antennas. A typical example is the implementation of data links using the Radar or the EWS.

Analysis of K-distributed sea clutter and thermal noise in high range and Doppler resolution radar data

This paper deals with the distribution of signal received by airborne radar in Doppler domain for maritime surveillance mission. It is composed of thermal noise and sea clutter which its intensity may be described by a compound K-distribution. The data used was recorded in high range and Doppler resolution by monostatic coherent X-band radar above Mediterranean sea and Atlantic ocean. The statistics of the sea clutter plus noise distributions have been estimated by calculating the complementary cumulative density function of real data. The variation of the fitted shape parameter is compared and discussed in a wide range of data under various conditions.

Performance assessment of multi-channel radars using simulated sea clutter

The generation of synthetic environments, in particular clutter, greatly facilitates the characterization of the performance of radars. This is especially the case for radars operating over maritime areas where the sea clutter is highly dependent on the environmental conditions that cannot be controlled or predicted for assessment of performance in trials. Three levels of complexity of the clutter simulation are considered here, according to the different radar modes to be qualified. The first level relates to non-coherent radars while the other levels aim at stimulating coherent Doppler radars. The last level allows generating coherent signals on multiple channels, for instance to validate complex detection modes such as involving Space-Time dependencies (STAP).

Is Compressive Sensing really useful for radar

Compressive Sensing (CS) was originally developed to directly acquire a compressed description of a sparse scene. This can be possible provided that the sampling scheme meet certain criteria. In Radar applications, the main advantage highlighted in the literature is the reduction of the data-flow between the R.F. front-end and processing that would be intractable in number of cases. However thanks to the technological progresses in fast Analog to Digital Conversion (ADC) and subsequent digital processing, the real problem is not at this level except in some special cases. The real issue is that it is not always possible to sample the radar signal ideally for practical and uncontrollable reasons. So far, most of the work in the literature has focused on the mathematical aspect of the underlying L1 inverse problem. This paper shows some examples where the use of sparse or incomplete sampling is really justified. We also show that the inverse problem resolution based on the minimization of the L1 norm, even if it is elegant way to solve the problem, is not the only means to address the problem.

MIMO radar for sense and avoid for UAV

UAV are easily deployable platforms. Up to now they carry payloads (surveillance, combat) for military purposes in crisis or war time. For training, UAV are flown in special areas attributed in a limited space and a limited time slot. In the future, UAV will also be used for civilian tasks. For these reasons, UAV will have to be inserted in the general Air traffic and “Sense and Avoid” systems will be mandatory. Among the possible sensors, the radar is the most pertinent one: it is “all-weather” and provides accurate range, direction and closing speed. In this paper, a low cost solution based on the coherent “MIMO” principles is described. This solution allows the location of the radar within the UAV airframe without any moving parts, hence provides a high reliability level. The rationale of the proposed architecture is explained, then the enabling technologies and related waveforms are described.

Slow and small target detection in high sea states

This paper addresses the detection of small and slow craft with Maritime Radar. Fast target detection can be carried out using standard processing such as MMTI (Maritime Moving Target Indicator) regardless of the sea state. However, in case of slow moving targets in high sea state, these methods no longer work because of the intrinsic spreading of the sea clutter. After having summarized the statistical modelling of the sea clutter, in order to highlight its particularity especially when observed with high range resolution waveforms, the paper explains the interest of Track-Before-Detect (TBD) detectors for taking benefits of both high-resolution waveforms and sea clutter properties. Two TBD detectors are compared to standard detectors working on a single dwell.

Design of a multi-resolution phase-coded waveform in the presence of a colored Gaussian clutter

In current airborne radars, detection and identification are done with two distinct waveforms. However, while the radar switches from one function to another, the target scene can change. In this paper, we propose a hybrid waveform combining intra and interpulse phase codes. This waveform is first processed in a low-resolution “channel”. Then, if a target is detected, the received signal is reprocessed in a high-resolution “channel”. Given the above scenario and assuming that the received data are disturbed by a colored Gaussian clutter, we address the optimization of the phase codes by searching the Pareto front of a multi-objective optimization problem. Finally, we aim at analyzing the sensitivity of the Pareto front to the clutter properties. For this purpose, we study whether a first-order autoregressive (AR) modelling for the clutter in the high-resolution case is relevant or not.

Radar and Electronic Warfare cooperation: How to improve the system efficiency?

Up to now, combat aircrafts are fitted with Fire Control Radar (FCR), Electronic Warfare Systems (EWS), and some radio links. Each of these systems Is dedicated to a particular task and cooperation is reduced to a minimal exchange of information between them, so far. Major system performance enhancements are to be expected from close cooperation to other sensors. The future cooperations can be ordered in four stages: the first three stages lead progressively to a multi-function sensor. The last is the deployment, on a given platform, of compact multi-function sensors on a network basis. Another area of cooperation is the realization of RF functions currently provided by other devices using other antennas. A typical example is the implementation of data links using radar or the EWS.