Human Respiration Rate Estimation Using Ultra-wideband Distributed Cognitive Radar System

It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present a multi-ray propagation model for UWB signal,which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces,A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment.This model enables replication of time-varying multipath profiles due to the displacement of a human chest.Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate.The analytical framework can serve as a basis in the planning and evaluation of future rheasurement programs.We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture.

Cramer-Rao bound and signal-to-noise ratio gain in distributed coherent aperture radar

This paper studies the estimation performance of the coherent processing parameter （CPP）, including time delay differences and phase synchronization errors among different apertures of the distributed coherent aperture radar （DCAR）. Firstly, three architectures of signal processing in the DCAR are introduced. Secondly, the closed-form Cramer-Rao bound （CRB） of the CPP estimation is derived and compared. Then, the closed-form CRB is verified by numerical simulations. Finally, when the next generation radar works in a fully coherent mode, the closed-form signal-to-noise ratio （SNR） gain of the three architectures is presented.

Distributed inverse synthetic aperture radar imaging of ship target with complex motion

For ship targets with complex motion,it is difficult for the traditional monostatic inverse synthetic aperture radar(ISAR)imaging to improve the cross-range resolution by increasing of accumulation time.In this paper,a distributed ISAR imaging algorithm is proposed to improve the cross-range resolution for the ship target.Multiple stations are used to observe the target in a short time,thereby the effect of incoherence caused by the complex motion of the ship can be reduced.The signal model of ship target with three-dimensional(3-D)rotation is constructed firstly.Then detailed analysis about the improvement of crossrange resolution is presented.Afterward,we propose the methods of parameters estimation to solve the problem of the overlap or gap,which will cause a loss of resolution and is necessary for subsequent processing.Besides,the compressed sensing(CS)method is applied to reconstruct the echoes with gaps.Finally,numerical simulations are presented to verify the effectiveness and the robustness of the proposed algorithm.

Modified OMP method for multi-target parameter estimation in frequency-agile distributed MIMO radar

Introducing frequency agility into a distributed multipleinput multiple-output(MIMO)radar can significantly enhance its anti-jamming ability.However,it would cause the sidelobe pedestal problem in multi-target parameter estimation.Sparse recovery is an effective way to address this problem,but it cannot be directly utilized for multi-target parameter estimation in frequency-agile distributed MIMO radars due to spatial diversity.In this paper,we propose an algorithm for multi-target parameter estimation according to the signal model of frequency-agile distributed MIMO radars,by modifying the orthogonal matching pursuit(OMP)algorithm.The effectiveness of the proposed method is then verified by simulation results.

Distributed Radar Target Tracking with Low Communication Cost

In distributed radar,most of existing radar networks operate in the tracking fusion mode which combines radar target tracks for a higher positioning accuracy.However,as the filtering covariance matrix indicating positioning accuracy often occupies many bits,the communication cost from local sensors to the fusion is not always sufficiently low for some wireless communication chan-nels.This paper studies how to compress data for distributed tracking fusion algorithms.Based on the K-singular value decomposition(K-SVD)algorithm,a sparse coding algorithm is presented to sparsely represent the filtering covariance matrix.Then the least square quantization(LSQ)algo-rithm is used to quantize the data according to the statistical characteristics of the sparse coeffi-cients.Quantized results are then coded with an arithmetic coding method which can further com-press data.Numerical results indicate that this tracking data compression algorithm drops the com-munication bandwidth to 4%at the cost of a 16%root mean squared error(RMSE)loss.

Phase synchronization processing method for alternating bistatic mode in distributed SAR

In the distributed synthetic aperture radar （SAR）, the alternating bistatic mode can perform phase reference without a synchronization link between two satellites compared with the pulsed alternate synchronization method. The key of the phase synchronization processing is to extract the oscillator phase differences from the bistatic echoes. A signal model of phase synchronization in the alternating bistatic mode is presented. The phase synchronization processing method is then studied. To reduce the phase errors introduced by SAR imaging, a sub-aperture processing method is proposed. To generalize the sub-aperture processing method, an echo-domain processing method using correlation of bistatic echoes is proposed. Finally, the residual phase errors of the both proposed processing methods are analyzed. Simulation experiments validate the proposed phase synchronization processing method and its phase error analysis results.

Adapitive waveform design for distributed OFDM MIMO radar system in multi-target scenario

In order to improve detection and estimation performance of distributed OrthogonalFrequency-Division Multiplexing（OFDM） Multiple-Input Multiple-Output（MIMO） radar system in multi-target scene, we propose a novel approach of Adaptive Waveform Design（AWD） based on a constrained Multi-Objective Optimization（MOO）. The sparse measurement model of this radar system is derived, and the method based on decomposed Dantzig selectors is applied for the sparse recovery according to the block structures of the sparse vector and the system matrix. An AWD approach is proposed, which optimizes two objective functions, namely minimizing the upper bound of the recovery error and maximizing the weakest-target return, by adjusting the complex weights of the emitting waveform amplitudes. Several numerical simulations are provided and their results show that the detection and estimation performance of the radar system is improved significantly when this MOO-based AWD approach is applied to the distributed OFDM MIMO radar system. Especially, we verify the effectiveness of our AWD approach when the available samples are reduced severally and the technique of compressed sensing is introduced.

New deghosting method based on generalized triangulation

A new deghosting method based on the generalized triangulation is presented. First, two intersection points corresponding to the emitter position are obtained by utilizing two azimuth angles and two elevation angles from two jammed 3-D radars （or 2-D passive sensors）. Then, hypothesis testing based deghosting method in the multiple target scenarios is proposed using the two intersection points. In order to analyze the performance of the proposed method, the correct association probability of the true targets and the incorrect association probability of the ghost targets are defined. Finally, the Monte Carlo simulations are given for the proposed method compared with the hinge angle method in the cases of both two and three radars. The simulation results show that the proposed method has better performance than the hinge angle method in three radars case.

Time and phase synchronization using clutter observations in airborne distributed coherent aperture radars

Airborne Distributed Coherent Aperture Radar(ADCAR)is one of the most promising next-generation radars to significantly improve target detection and discrimination abilities.However,time and phase synchronization among unit radars should be done before an ADCAR is intended to cohere on a potential target.To address this problem,a time and phase synchronization technique using clutter observations is proposed in this paper.Clutter returns from different azimuths and elevations on the surface of the earth are employed to calibrate system uncertainties.Two stages are mainly considered:a scene registration among range-Doppler units from different transmit/receive pairs is performed to enhance the clutter coherence in the first stage,followed by a joint estimation of those synchronization errors in the second stage.To relieve the computational burden,a novel Separable and Sequential Estimation(SSE)method is provided to separate the unknowns at the sacrifice of a range-Doppler unit.Moreover,performance analyses including the clutter coherence ability,estimation lower bound,and signal coherence loss are also performed.Finally,simulation results indicate that ADCAR time and phase synchronization is realized by using our methods.

Detection performance analysis for MIMO radar with distributed apertures in Gaussian colored noise

This paper establishes the classic linear model of signal of the MIMO radar system with distributed apertures. Based on this model, the design principle and detection performance of MIMO radar detector is investigated under conditions of Gaussian colored noise and partially correlated observation channels. First, the research on design principle of detector shows that the clutter suppression and matched filtering can be independently implemented at each receiving aperture, which greatly reduces the difficulty in implementation of these detectors. Based on these results, a Max detector is proposed for the case where partial channels are disabled due to strong noise and stealth techniques. The second part is the performance analysis of detector. The Fishier divergence coefficient and the statistical equivalent decomposition of limit statistics are used to theoretically analyze the detection performance of AMF detector, and then the analytical expressions of the detection performance of the AMF detector is derived. Analysis results show that both the colored nature of noise and the correlation among observation channels can reduce the capability of spatial diversity of the MIMO radar system, change the target RCSs among observation channels from quick fluctuation to slow fluctuation, and degenerate the detection performance of this radar system into that of the phased array radar system at high signal-to-noise ratio.

Nonuniform Three-dimensional Configuration Distributed SAR Signal Reconstruction Clutter Suppression

This paper deals with the problem of clutter suppression in spaceborne distributed synthetic aperture radar （D-SAR） with nonuniform three-dimensional （3D） configuration geometry. In order to make a breakthrough of the configuration limitation of the traditional space time adaptive processing （STAP） based on uniform array and improve the inhomogeneous clutter suppres- sion performance, this paper considers signal reconstrtiction technique using array interpolation to process the D-SAR signal. An array interpolation signal reconstruction method based on pitching-partition is derived then a signal reconstruction 3D-STAP clutter suppression method applied to nonuniform 3D configuration is proposed. In particular, the proposed method is compared with conventional methods and the performance analysis is carried out based on simulations. The improvement factor （IF） for clutter suppression is imported and reported as a benchmark on the clutter suppression effect.

Analysis of the Microphysical Properties of a Stratiform Rain Event Using an L-Band Profiler Radar

This paper investigates spatial and temporal distributions of the microphysical properties of precipitating stratiform clouds based on Doppler spectra of rain particles observed by an L-band profiler radar.The retrieval of raindrop size distributions（RSDs） is accomplished through eliminating vertical air motion and isolating the terminal fall velocity of raindrops in the observed Doppler velocity spectrum.The microphysical properties of raindrops in a broad stratiform region with weak convective cells are studied using data collected from a 1320-MHz wind profiler radar in Huayin,Shaanxi Province on 14 May 2009.RSDs and gamma function parameters are retrieved at altitudes between 700 and 3000 m above the surface,below a melting layer.It is found that the altitude of the maximum number of raindrops was closely related to the surface rain rate.The maximum number of large drops was observed at lower altitudes earlier in the precipitation event but at higher altitudes in later periods,suggesting decreases in the numbers of large and medium size raindrops.These decreases may have been caused by the breakup of larger drops and evaporation of smaller drops as they fell.The number of medium size drops decreased with increasing altitude.The relationship between reflectivity and liquid water content during this precipitation event was Z = 1.69×10~4M^（1.5）,and the relationship between reflectivity and rain intensity was Z = 256I^（1.4）.