2014 Vol. 3, No. 5

Paper
Radar Target Recognition (RTR) is one of the most important needs of modern and future airborne surveillance radars, and it is still one of the key technologies of radar. The majority of present algorithms are based on wide-band radar signal, which not only needs high performance radar system and high target Signal-to-Noise Ratio (SNR), but also is sensitive to angle between radar and target. Low-Resolution Airborne Surveillance Radar (LRASR) in downward-looking mode, slow flying aircraft and ground moving truck have similar Doppler velocity and Radar Cross Section (RCS), leading to the problem that LRASR air/ground moving targets can not be distinguished, which also disturbs detection, tracking, and classification of low altitude slow flying aircraft to solve these issues, an algorithm based on narrowband fractal feature and phase modulation feature is presented for LRASR air/ground moving targets classification. Real measured data is applied to verify the algorithm, the classification results validate the proposed method, helicopters and truck can be well classified, the average discrimination rate is more than 89% when SNR 15 dB. Radar Target Recognition (RTR) is one of the most important needs of modern and future airborne surveillance radars, and it is still one of the key technologies of radar. The majority of present algorithms are based on wide-band radar signal, which not only needs high performance radar system and high target Signal-to-Noise Ratio (SNR), but also is sensitive to angle between radar and target. Low-Resolution Airborne Surveillance Radar (LRASR) in downward-looking mode, slow flying aircraft and ground moving truck have similar Doppler velocity and Radar Cross Section (RCS), leading to the problem that LRASR air/ground moving targets can not be distinguished, which also disturbs detection, tracking, and classification of low altitude slow flying aircraft to solve these issues, an algorithm based on narrowband fractal feature and phase modulation feature is presented for LRASR air/ground moving targets classification. Real measured data is applied to verify the algorithm, the classification results validate the proposed method, helicopters and truck can be well classified, the average discrimination rate is more than 89% when SNR 15 dB.
The micro-motion is combined with the high velocity of translation motion for ballistic targets. The translation motion should be compensated for micro-Doppler information extraction. A new method based on delay conjugate multiplication is proposed to compensate the translation motion of ballistic target. By delay conjugate multiplication of the received signal, the micro-Doppler information are canceled out and the translation motion parameters estimation problem is transformed as an multi-polynomial phase signal parameters estimation problem. Thus, the translation parameters can be estimated. Simulation results suggest that the proposed algorithm can achieve high-precision compensation for ballistic targets under low SNR. The micro-motion is combined with the high velocity of translation motion for ballistic targets. The translation motion should be compensated for micro-Doppler information extraction. A new method based on delay conjugate multiplication is proposed to compensate the translation motion of ballistic target. By delay conjugate multiplication of the received signal, the micro-Doppler information are canceled out and the translation motion parameters estimation problem is transformed as an multi-polynomial phase signal parameters estimation problem. Thus, the translation parameters can be estimated. Simulation results suggest that the proposed algorithm can achieve high-precision compensation for ballistic targets under low SNR.
An important standard to measure the effectiveness of radar acquisition systems is the accuracy of target parameter estimation. To solve the estimation problem, the echo model of moving targets is established and the FRactional Fourier Transform (FRFT) is subsequently used to estimate the acceleration; further, data fusion is used to raise estimation accuracy. Finally, Range Cell Migration (RCM) and Doppler ambiguity are solved by using the Keystone transform and the ambiguity channels based on the estimated acceleration. The simulation results show high accuracy, complexity, and noise robustness. An important standard to measure the effectiveness of radar acquisition systems is the accuracy of target parameter estimation. To solve the estimation problem, the echo model of moving targets is established and the FRactional Fourier Transform (FRFT) is subsequently used to estimate the acceleration; further, data fusion is used to raise estimation accuracy. Finally, Range Cell Migration (RCM) and Doppler ambiguity are solved by using the Keystone transform and the ambiguity channels based on the estimated acceleration. The simulation results show high accuracy, complexity, and noise robustness.
An important bottleneck in spatial spectrum estimation theory is array errors. A new error self-calibration method is presented on the basis of active error calibration and online self-calibration theories. An algorithm combining Direction Of Arrival (DOA) estimation and array complex gain error calibration is developed using an auxiliary source without accurate spatial location information and numerical optimization calculation; the error calibration parameters can be used in the following spatial spectrum estimation. The method has a higher veracity than the active correction algorithm and is an offline calculation procedure, having the advantage of small computation amount, similar to the online self-calibration method, and avoiding accurate spatial location information in classical active calibration method. An important bottleneck in spatial spectrum estimation theory is array errors. A new error self-calibration method is presented on the basis of active error calibration and online self-calibration theories. An algorithm combining Direction Of Arrival (DOA) estimation and array complex gain error calibration is developed using an auxiliary source without accurate spatial location information and numerical optimization calculation; the error calibration parameters can be used in the following spatial spectrum estimation. The method has a higher veracity than the active correction algorithm and is an offline calculation procedure, having the advantage of small computation amount, similar to the online self-calibration method, and avoiding accurate spatial location information in classical active calibration method.
Zero Memory NonLinearity (ZMNL) and Spherically Invariant Random Process (SIRP) are two commonly used methods in K-distribution clutter simulations. An improved simulation method, which adds abranch of Gamma-distributed variable and extends the shape parameter to arbitrary positive real, is proposed to address the clutter simulation error in the conventional ZMNL method. To reduce the computation required for the conventional SIRP method, an improved method of modulation variable generation is also proposed, what avoids large computations for solving nonlinear equations and improves the simulation speed. The simulation results verify the effectiveness of the improved methods. Zero Memory NonLinearity (ZMNL) and Spherically Invariant Random Process (SIRP) are two commonly used methods in K-distribution clutter simulations. An improved simulation method, which adds abranch of Gamma-distributed variable and extends the shape parameter to arbitrary positive real, is proposed to address the clutter simulation error in the conventional ZMNL method. To reduce the computation required for the conventional SIRP method, an improved method of modulation variable generation is also proposed, what avoids large computations for solving nonlinear equations and improves the simulation speed. The simulation results verify the effectiveness of the improved methods.
Radar coincidence imaging is a new method for high-resolution staring imaging. First, the mathematical model is constructed. Second, the theoretical error for radar coincidence imaging in the presence of noise is derived using the parametric imaging method. Third, the factors that affect the error are analyzed. Fourth, the sparse reconstruction algorithm is used to perform numerical simulations of radar coincidence imaging with different parameters. Finally, the effects of signal bandwidth, array configuration, size of the imaging unit, and target complexity on image error in the presence of noise are discussed. This study provides the theoretical framework for parameters selection and SNR requirements for radar coincidence imaging systems. Radar coincidence imaging is a new method for high-resolution staring imaging. First, the mathematical model is constructed. Second, the theoretical error for radar coincidence imaging in the presence of noise is derived using the parametric imaging method. Third, the factors that affect the error are analyzed. Fourth, the sparse reconstruction algorithm is used to perform numerical simulations of radar coincidence imaging with different parameters. Finally, the effects of signal bandwidth, array configuration, size of the imaging unit, and target complexity on image error in the presence of noise are discussed. This study provides the theoretical framework for parameters selection and SNR requirements for radar coincidence imaging systems.
Integration of radar and communication systems based on OFDM signals results in large Peak-to-Average Power Ratio (PAPR). Limited by the code rate, algorithm that use the Golay sequence code to restrain PAPR can only be applied under the condition of a few subcarriers. This study proposes an algorithm to restrain the PAPR of systems with a large number of subcarriers. The algorithm combines the group parallel code with the optimization of weight coefficients. First, bit streams are divided into several groups of parallel bits. Next, every group proceeds with Golay sequence coding, data symbol modulating and inverse Fourier transform. Finally, the parallel result is combined with an OFDM symbol. Before the parallel data are combined, several weight coefficients for every group are introduced; thus, the system has several candidate symbols for transmitting. Then the symbol with minimum PAPR is then selected as the transmitting signal, and the PAPR of the whole system is reduced. PAPR performance, Bit Error Radio (BER) and wideband ambiguity function of three block methods with different coding rate are also simulated. The simulations show that the PAPR of the system decreases and the BER performance improves significantly. The signal exhibits a thumbtack ambiguity function, which suggests good resolution and accuracy for distance and velocity measurements. Integration of radar and communication systems based on OFDM signals results in large Peak-to-Average Power Ratio (PAPR). Limited by the code rate, algorithm that use the Golay sequence code to restrain PAPR can only be applied under the condition of a few subcarriers. This study proposes an algorithm to restrain the PAPR of systems with a large number of subcarriers. The algorithm combines the group parallel code with the optimization of weight coefficients. First, bit streams are divided into several groups of parallel bits. Next, every group proceeds with Golay sequence coding, data symbol modulating and inverse Fourier transform. Finally, the parallel result is combined with an OFDM symbol. Before the parallel data are combined, several weight coefficients for every group are introduced; thus, the system has several candidate symbols for transmitting. Then the symbol with minimum PAPR is then selected as the transmitting signal, and the PAPR of the whole system is reduced. PAPR performance, Bit Error Radio (BER) and wideband ambiguity function of three block methods with different coding rate are also simulated. The simulations show that the PAPR of the system decreases and the BER performance improves significantly. The signal exhibits a thumbtack ambiguity function, which suggests good resolution and accuracy for distance and velocity measurements.
Special Topic Papers:Synthetic Aperture Radar (SAR)
For Through-the-Wall Imaging Radar (TWIR), wall clutter is critical for detecting target signals behind a wall. For a system with a sparse antenna array, the lack of observation channels makes it more difficult to separate the target signals and wall clutter. On the basis of fluctuation of the range profile in real transmit/receive channels, this paper proposes to use Independent Component Analysis (ICA) on multiple down-range observations of each transmit/receive channel to remove the wall clutter. The simulation and experimental results show that the proposed method effectively separate target and clutter components, even though the signal-to-clutter ratio is only -30 dB. For Through-the-Wall Imaging Radar (TWIR), wall clutter is critical for detecting target signals behind a wall. For a system with a sparse antenna array, the lack of observation channels makes it more difficult to separate the target signals and wall clutter. On the basis of fluctuation of the range profile in real transmit/receive channels, this paper proposes to use Independent Component Analysis (ICA) on multiple down-range observations of each transmit/receive channel to remove the wall clutter. The simulation and experimental results show that the proposed method effectively separate target and clutter components, even though the signal-to-clutter ratio is only -30 dB.
Multi-channel in azimuth is a technique to achieve high-resolution as well as wide-swath in Synthetic Aperture Radar (SAR) systems. Channel error is inevitable in multi-channel systems and it induces blurring in subsequent SAR imagery. Existing compensation approaches are sensitive to system parameters as well as the imaging scenes. Uncertainty of the parameters impacts the validation of these algorithms. In this paper, an improved approach is presented to remove the channel error. Based on the error form, this approach models channel error as three parts: the range gain error, the pulse sampling clock error, and the transmission phase error. The range gain error and the pulse sampling clock error are removed alternately. Then the proposed approach uses cost function to estimate the transmission phase error so that it is independent from the imaging scene. Point target simulations are carried out to investigate the performance, and real data comparison experiments are carried out to verify this approach. Multi-channel in azimuth is a technique to achieve high-resolution as well as wide-swath in Synthetic Aperture Radar (SAR) systems. Channel error is inevitable in multi-channel systems and it induces blurring in subsequent SAR imagery. Existing compensation approaches are sensitive to system parameters as well as the imaging scenes. Uncertainty of the parameters impacts the validation of these algorithms. In this paper, an improved approach is presented to remove the channel error. Based on the error form, this approach models channel error as three parts: the range gain error, the pulse sampling clock error, and the transmission phase error. The range gain error and the pulse sampling clock error are removed alternately. Then the proposed approach uses cost function to estimate the transmission phase error so that it is independent from the imaging scene. Point target simulations are carried out to investigate the performance, and real data comparison experiments are carried out to verify this approach.
The method of generating the SAR raw data of complex airport scenes is studied in this paper. A formulation of the SAR raw signal model of airport scenes is given. Via generating the echoes from the background, aircrafts and buildings, respectively, the SAR raw data of the unified SAR imaging geometry is obtained from their vector additions. The multipath scattering and the shadowing between the background and different ground covers of standing airplanes and buildings are analyzed. Based on the scattering characteristics, coupling scattering models and SAR raw data models of different targets are given, respectively. A procedure is given to generate the SAR raw data of airport scenes. The SAR images from the simulated raw data demonstrate the validity of the proposed method. The method of generating the SAR raw data of complex airport scenes is studied in this paper. A formulation of the SAR raw signal model of airport scenes is given. Via generating the echoes from the background, aircrafts and buildings, respectively, the SAR raw data of the unified SAR imaging geometry is obtained from their vector additions. The multipath scattering and the shadowing between the background and different ground covers of standing airplanes and buildings are analyzed. Based on the scattering characteristics, coupling scattering models and SAR raw data models of different targets are given, respectively. A procedure is given to generate the SAR raw data of airport scenes. The SAR images from the simulated raw data demonstrate the validity of the proposed method.
In this paper, when the azimuth direction of polarimetric Synthetic Aperature Radars (SAR) differs from the planting direction of crops, the double bounce of the incident electromagnetic waves from the terrain surface to the growing crops is investigated and compared with the normal double bounce. Oriented dihedral scattering model is developed to explain the investigated double bounce and is introduced into the Freeman-Durden decomposition. The decomposition algorithm corresponding to the improved decomposition is then proposed. The airborne polarimetric SAR data for agricultural land covering two flight tracks are chosen to validate the algorithm; the decomposition results show that for agricultural vegetated land, the improved Freeman-Durden decomposition has the advantage of increasing the decomposition coherency among the polarimetric SAR data along the different flight tracks. In this paper, when the azimuth direction of polarimetric Synthetic Aperature Radars (SAR) differs from the planting direction of crops, the double bounce of the incident electromagnetic waves from the terrain surface to the growing crops is investigated and compared with the normal double bounce. Oriented dihedral scattering model is developed to explain the investigated double bounce and is introduced into the Freeman-Durden decomposition. The decomposition algorithm corresponding to the improved decomposition is then proposed. The airborne polarimetric SAR data for agricultural land covering two flight tracks are chosen to validate the algorithm; the decomposition results show that for agricultural vegetated land, the improved Freeman-Durden decomposition has the advantage of increasing the decomposition coherency among the polarimetric SAR data along the different flight tracks.
Small size, light weight, and low power are presently the directions in SAR development. The microSAR platform is small and light, which results in track deviations because of air flow. The large motion error strongly affects the quality of SAR images. Therefore, high-precision motion compensation is important to SAR image processing. Motion error results in phase and envelope errors. Traditional motion compensation algorithms often ignore the space variance of the envelope error. When the motion error is large, the space-variant envelope error affects the image quality. This study proposes a high-precision motion compensation method based on the subaperture envelope error correction for SAR. The proposed method minimizes the effect of the space-variant envelope error and improves the image quality. Simulations and experimental data processing validate the correctness and effectiveness of the proposed algorithm. Small size, light weight, and low power are presently the directions in SAR development. The microSAR platform is small and light, which results in track deviations because of air flow. The large motion error strongly affects the quality of SAR images. Therefore, high-precision motion compensation is important to SAR image processing. Motion error results in phase and envelope errors. Traditional motion compensation algorithms often ignore the space variance of the envelope error. When the motion error is large, the space-variant envelope error affects the image quality. This study proposes a high-precision motion compensation method based on the subaperture envelope error correction for SAR. The proposed method minimizes the effect of the space-variant envelope error and improves the image quality. Simulations and experimental data processing validate the correctness and effectiveness of the proposed algorithm.
This study examines the imaging problems in airborne synthetic aperture ladar with single detector and dual detectors along tracks under platform vibration condition. Because platform vibrations affect imaging processing for short intervals negligibly, a method uniting the subaperture imaging and phase gradient autofocus is considered for single-detector ladar. To obtain long stripmap images in azimuth, the stripmap phase gradient autofocus method and the subaperture image mosaic process using Doppler centroid estimation are used. Their performance is analyzed and compared. Considering the shortage of single-detector ladar, a method based on along-track dual-detector interferometric processing is proposed to estimate and compensate for the vibration phase error. The simulation verifies the effectiveness of the proposed methods. This study examines the imaging problems in airborne synthetic aperture ladar with single detector and dual detectors along tracks under platform vibration condition. Because platform vibrations affect imaging processing for short intervals negligibly, a method uniting the subaperture imaging and phase gradient autofocus is considered for single-detector ladar. To obtain long stripmap images in azimuth, the stripmap phase gradient autofocus method and the subaperture image mosaic process using Doppler centroid estimation are used. Their performance is analyzed and compared. Considering the shortage of single-detector ladar, a method based on along-track dual-detector interferometric processing is proposed to estimate and compensate for the vibration phase error. The simulation verifies the effectiveness of the proposed methods.
Reviews
With the development of high speed digital processor and solid state power electronics, more flexible waveforms become feasible to achieve by modern radar systems. In fact, the choice of waveforms has a significant impact on the performance of radar systems. In this paper, we review the conventional radar waveform design as well as explore the new generation of waveforms via different theoretical methods, including the most recent wavelet based waveforms. It is shown that the waveform design supports the radar advancement for more intelligent and divergent applications. In this endeavor, radar waveform design plays an even more important role in reaching specific purposes, in addition to range and speed detections, and further improves the performance and application scopes of radar systems. With the development of high speed digital processor and solid state power electronics, more flexible waveforms become feasible to achieve by modern radar systems. In fact, the choice of waveforms has a significant impact on the performance of radar systems. In this paper, we review the conventional radar waveform design as well as explore the new generation of waveforms via different theoretical methods, including the most recent wavelet based waveforms. It is shown that the waveform design supports the radar advancement for more intelligent and divergent applications. In this endeavor, radar waveform design plays an even more important role in reaching specific purposes, in addition to range and speed detections, and further improves the performance and application scopes of radar systems.