We investigate finite sample size performance of the eigenvector projection method when applied to space-time adaptive processing (STAP). A theoretical analysis of the expectation of the signal to interference plus noise ratio (SINR) for the eigenvector projection technique is presented. This gives insight into the the problem of determining the optimum choice of the projected clutter subspace. An estimator of the sample-size dependent optimum subspace dimension, which can be significantly smaller than the clutter rank, is also presented. This result, combined with near-optimal eigenvector-free projection techniques with minimal sample support, helps in reducing the computational burden significantly.
{"title":"Theoretical analysis of small sample size behaviour of eigenvector projection technique applied to STAP","authors":"B. Balaji, C. Gierull","doi":"10.1109/NRC.2002.999747","DOIUrl":"https://doi.org/10.1109/NRC.2002.999747","url":null,"abstract":"We investigate finite sample size performance of the eigenvector projection method when applied to space-time adaptive processing (STAP). A theoretical analysis of the expectation of the signal to interference plus noise ratio (SINR) for the eigenvector projection technique is presented. This gives insight into the the problem of determining the optimum choice of the projected clutter subspace. An estimator of the sample-size dependent optimum subspace dimension, which can be significantly smaller than the clutter rank, is also presented. This result, combined with near-optimal eigenvector-free projection techniques with minimal sample support, helps in reducing the computational burden significantly.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114592115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper develops a method for estimating the sparse array mutual coupling matrix and sensor gains/phases using a signal source at unknown directions. The sparsity of the mutual coupling matrix results from the recognition that the mutual coupling between array elements is inversely related to their separation and may be negligible for elements separated by a few wavelengths. We remove the restriction that the signal test source directions must be known, as required in an earlier recent work by the author (see Jaffer, A.G., Proc. 35th Asilomar Conference on Signals, Systems and Computers, 2001). A fast converging iterative method is developed which estimates the directions and the sparse mutual coupling matrix and sensor gains/phases. Computer simulation results are presented to demonstrate the utility of the method.
本文提出了一种利用未知方向的信号源估计稀疏阵列互耦矩阵和传感器增益/相位的方法。互耦矩阵的稀疏性是由于认识到阵列元素之间的互耦与它们的距离成反比，并且对于相距几个波长的元素可以忽略不计。我们取消了信号测试源方向必须已知的限制，正如作者最近早期工作所要求的那样(见Jaffer, a.g.， Proc. 35 Asilomar会议上的信号，系统和计算机，2001)。提出了一种快速收敛迭代估计方向、稀疏互耦矩阵和传感器增益/相位的方法。计算机仿真结果验证了该方法的有效性。
{"title":"Sparse mutual coupling matrix and sensor gain/phase estimation for array auto-calibration","authors":"A. Jaffer","doi":"10.1109/NRC.2002.999734","DOIUrl":"https://doi.org/10.1109/NRC.2002.999734","url":null,"abstract":"This paper develops a method for estimating the sparse array mutual coupling matrix and sensor gains/phases using a signal source at unknown directions. The sparsity of the mutual coupling matrix results from the recognition that the mutual coupling between array elements is inversely related to their separation and may be negligible for elements separated by a few wavelengths. We remove the restriction that the signal test source directions must be known, as required in an earlier recent work by the author (see Jaffer, A.G., Proc. 35th Asilomar Conference on Signals, Systems and Computers, 2001). A fast converging iterative method is developed which estimates the directions and the sparse mutual coupling matrix and sensor gains/phases. Computer simulation results are presented to demonstrate the utility of the method.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114695999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In over-the-horizon radar (OTHR) moving target detection, the signal to clutter ratio (SCR) is low. One method to detect a moving target is to first reject the clutter and improve the SCR before the detection, such as the adaptive Fourier transform developed by Root (see SPIE Conference, San Diego, p.19-24, July 1998) when a target moves uniformly. When a target does not move uniformly, the Fourier based techniques for the target detection including super resolution techniques may not work well. We replace the Fourier transform by the adaptive chirplet transform in the Doppler processing in OTHR when a target moves non-uniformly.
在超视距雷达(OTHR)运动目标检测中，信杂比(SCR)较低。检测运动目标的一种方法是在检测前首先抑制杂波并提高SCR，如Root在目标均匀运动时开发的自适应傅立叶变换(参见SPIE Conference, San Diego, p.19-24, July 1998)。当目标运动不均匀时，基于傅立叶的目标检测技术包括超分辨率技术可能无法很好地工作。当目标运动不均匀时，用自适应小波变换代替傅立叶变换进行多普勒处理。
{"title":"Moving target detection in over-the-horizon radar using adaptive chirplet transform","authors":"Genyuan Wang, X. Xia, B. Root, V. Chen","doi":"10.1109/NRC.2002.999697","DOIUrl":"https://doi.org/10.1109/NRC.2002.999697","url":null,"abstract":"In over-the-horizon radar (OTHR) moving target detection, the signal to clutter ratio (SCR) is low. One method to detect a moving target is to first reject the clutter and improve the SCR before the detection, such as the adaptive Fourier transform developed by Root (see SPIE Conference, San Diego, p.19-24, July 1998) when a target moves uniformly. When a target does not move uniformly, the Fourier based techniques for the target detection including super resolution techniques may not work well. We replace the Fourier transform by the adaptive chirplet transform in the Doppler processing in OTHR when a target moves non-uniformly.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117120765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In ground surveillance from an airborne or space-based radar it is desirable to be able to detect small and slowly moving targets, within severe ground clutter. For operational moving target indication (MTI) systems the clutter filter coefficients have to be updated frequently due to rapidly changing interference environment. This paper examines the small sample size performance of different fast fully adaptive space-time processors (STAP) and compares it to the optimum-detector performance. These previously proposed techniques, named matrix transformation based projection (MTP) and lean matrix inversion (LMI), were originally developed to provide fast jammer suppression in phased array radars with many elements. For this application they have been proven to operate with near-optimum performance, yet with a computational expense extremely reduced from that of the optimum detector in most practical cases. The investigation herein focuses on the performance achieved when only a very few data samples are available to adapt (update) the clutter filter coefficient.
{"title":"Application of fast projection techniques without eigenanalysis to STAP","authors":"C. Gierull, B. Balaji","doi":"10.1109/NRC.2002.999748","DOIUrl":"https://doi.org/10.1109/NRC.2002.999748","url":null,"abstract":"In ground surveillance from an airborne or space-based radar it is desirable to be able to detect small and slowly moving targets, within severe ground clutter. For operational moving target indication (MTI) systems the clutter filter coefficients have to be updated frequently due to rapidly changing interference environment. This paper examines the small sample size performance of different fast fully adaptive space-time processors (STAP) and compares it to the optimum-detector performance. These previously proposed techniques, named matrix transformation based projection (MTP) and lean matrix inversion (LMI), were originally developed to provide fast jammer suppression in phased array radars with many elements. For this application they have been proven to operate with near-optimum performance, yet with a computational expense extremely reduced from that of the optimum detector in most practical cases. The investigation herein focuses on the performance achieved when only a very few data samples are available to adapt (update) the clutter filter coefficient.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"33 1-2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116721800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The use of time and frequency references disciplined to GPS has been studied in the context of use in multistatic radar. Several reference units with civilian GPS receivers were tested. Differences in 1PPS fluctuations were observed that would result in ranging errors when stable GPS signals were received. If GPS signals were lost further control of reference output depends on the stability of the reference unit. Drift in frequency and corresponding time deviation were observed according to reference quality. The stable rubidium references were found to give reliable synchronization output for a long time without synchronization.
{"title":"Time and frequency synchronization in multistatic radar. Consequences to usage of GPS disciplined references with and without GPS signals","authors":"T. Johnsen","doi":"10.1109/NRC.2002.999711","DOIUrl":"https://doi.org/10.1109/NRC.2002.999711","url":null,"abstract":"The use of time and frequency references disciplined to GPS has been studied in the context of use in multistatic radar. Several reference units with civilian GPS receivers were tested. Differences in 1PPS fluctuations were observed that would result in ranging errors when stable GPS signals were received. If GPS signals were lost further control of reference output depends on the stability of the reference unit. Drift in frequency and corresponding time deviation were observed according to reference quality. The stable rubidium references were found to give reliable synchronization output for a long time without synchronization.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127421217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The use of adaptive algorithms to mitigate the detrimental effects of noise on receivers employing antenna arrays is instrumental in modern day radar systems applications. In most of these algorithms, the target is assumed to be confined to only one range cell. Under practical operating conditions, the target can actually be distributed across several range cells. This signal contamination causes the performance of the adaptive algorithm to degrade. Also, a covariance matrix is used for clutter-plus-noise in the design of the adaptive algorithm. This quantity is usually characterized by using samples taken from range cells surrounding the test cell. Performance suffers if the underlying test cell covariance matrix is different from the average covariance matrix of the surrounding range cells. We analyze a space-time adaptive processing (STAP) algorithm designed to utilize signal contamination to the advantage of the receiver. Expressions for performance, incorporating the possibility of covariance matrix mismatch, are developed for such distributed target scenarios. Numerical analysis illustrates that the presented algorithm functions significantly better than traditional STAP algorithms in signal contaminated environments. This investigation also shows how variations in the parameters that describe covariance matrix mismatch affect performance.
{"title":"Performance characterization of space-time adaptive processing algorithms for distributed target detection in non-ideal environments","authors":"K. McDonald, Rick S. Blum","doi":"10.1109/NRC.2002.999735","DOIUrl":"https://doi.org/10.1109/NRC.2002.999735","url":null,"abstract":"The use of adaptive algorithms to mitigate the detrimental effects of noise on receivers employing antenna arrays is instrumental in modern day radar systems applications. In most of these algorithms, the target is assumed to be confined to only one range cell. Under practical operating conditions, the target can actually be distributed across several range cells. This signal contamination causes the performance of the adaptive algorithm to degrade. Also, a covariance matrix is used for clutter-plus-noise in the design of the adaptive algorithm. This quantity is usually characterized by using samples taken from range cells surrounding the test cell. Performance suffers if the underlying test cell covariance matrix is different from the average covariance matrix of the surrounding range cells. We analyze a space-time adaptive processing (STAP) algorithm designed to utilize signal contamination to the advantage of the receiver. Expressions for performance, incorporating the possibility of covariance matrix mismatch, are developed for such distributed target scenarios. Numerical analysis illustrates that the presented algorithm functions significantly better than traditional STAP algorithms in signal contaminated environments. This investigation also shows how variations in the parameters that describe covariance matrix mismatch affect performance.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126730946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An overview of a complete simulation of an active electronically scanned array (AESA) radar system is given. The Airborne Radar Environment Simulation (ARES) tool has been developed to represent signals emanating from the radar's environment at the sub-array level. This data forms the input to a test bed simulation in which signal processing algorithms can be developed, in particular adaptive beam forming (ABF) and space-time adaptive processing (STAP) techniques which make use of the sub-array signals. Examples of the outputs from the simulations are presented. The philosophy and methodology of radar systems design and development using simulations is discussed.
{"title":"Sub-array level simulation of an active electronically scanned array radar for integrated system design","authors":"N. Ramsey, C. McComb, D. Greig","doi":"10.1109/NRC.2002.999726","DOIUrl":"https://doi.org/10.1109/NRC.2002.999726","url":null,"abstract":"An overview of a complete simulation of an active electronically scanned array (AESA) radar system is given. The Airborne Radar Environment Simulation (ARES) tool has been developed to represent signals emanating from the radar's environment at the sub-array level. This data forms the input to a test bed simulation in which signal processing algorithms can be developed, in particular adaptive beam forming (ABF) and space-time adaptive processing (STAP) techniques which make use of the sub-array signals. Examples of the outputs from the simulations are presented. The philosophy and methodology of radar systems design and development using simulations is discussed.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126853999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The potential to model sea clutter radar returns using chaos theory is examined. Chaotic systems display qualitative similarities to sea clutter returns such as broad flat spectra, boundedness and irregular temporal behaviour. In this report several key parameters of chaotic systems, namely correlation dimension, Lyapunov spectrum and Lyapunov dimension are calculated from real sea clutter returns and found to be consistent with a chaotic interpretation. The airborne high resolution data (less than one metre) produces a correlation coefficient with an average value of 4.63 and an embedding dimension of 6-7. Lyapunov dimensions are consistent with correlation values. A local linear technique and a radial basis function (RBF) are used to construct a one step non-linear predictor. A mean square error (MSE) of approximately 0.0032 between the predicted and normalized (i.e. maximum +/-1 range) real time series is measured.
{"title":"Chaotic behaviour and non-linear prediction of airborne radar sea clutter data","authors":"M. McDonald, V. Varadan, H. Leung","doi":"10.1109/NRC.2002.999740","DOIUrl":"https://doi.org/10.1109/NRC.2002.999740","url":null,"abstract":"The potential to model sea clutter radar returns using chaos theory is examined. Chaotic systems display qualitative similarities to sea clutter returns such as broad flat spectra, boundedness and irregular temporal behaviour. In this report several key parameters of chaotic systems, namely correlation dimension, Lyapunov spectrum and Lyapunov dimension are calculated from real sea clutter returns and found to be consistent with a chaotic interpretation. The airborne high resolution data (less than one metre) produces a correlation coefficient with an average value of 4.63 and an embedding dimension of 6-7. Lyapunov dimensions are consistent with correlation values. A local linear technique and a radial basis function (RBF) are used to construct a one step non-linear predictor. A mean square error (MSE) of approximately 0.0032 between the predicted and normalized (i.e. maximum +/-1 range) real time series is measured.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124504874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this research, we propose techniques for the construction of frequency coding sequences that give rise to frequency coded waveforms having ambiguity functions with a clear area-containing no sidelobes-in a connected region surrounding the main lobe. In this sense, the proposed sequences have excellent delay-Doppler resolution properties and achieve locally optimal ambiguity functions in the region surrounding the main lobe. These sequences are called pushing sequences. First, two important properties of pushing sequences are investigated: the group D/sub 4/ dihedral symmetry property and the frequency omission property. We also note that Costas sequences have these two properties and the implications of this are investigated. Next, we show how to construct pushing sequences having ambiguity functions with arbitrary-size clear areas. Finally, we analyze the sidelobe distribution and provide the general form of all sidelobe peak positions, and both the lower and upper bound of each sidelobe peak level.
{"title":"Frequency coded waveforms for enhanced delay-Doppler resolution","authors":"Chieh-Fu Chang, M. Bell","doi":"10.1109/NRC.2002.999714","DOIUrl":"https://doi.org/10.1109/NRC.2002.999714","url":null,"abstract":"In this research, we propose techniques for the construction of frequency coding sequences that give rise to frequency coded waveforms having ambiguity functions with a clear area-containing no sidelobes-in a connected region surrounding the main lobe. In this sense, the proposed sequences have excellent delay-Doppler resolution properties and achieve locally optimal ambiguity functions in the region surrounding the main lobe. These sequences are called pushing sequences. First, two important properties of pushing sequences are investigated: the group D/sub 4/ dihedral symmetry property and the frequency omission property. We also note that Costas sequences have these two properties and the implications of this are investigated. Next, we show how to construct pushing sequences having ambiguity functions with arbitrary-size clear areas. Finally, we analyze the sidelobe distribution and provide the general form of all sidelobe peak positions, and both the lower and upper bound of each sidelobe peak level.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125266978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We address polarimetric adaptive detection of targets embedded in compound-Gaussian clutter with unknown covariance matrix. To this end we assume that a set of secondary data, free of signal components and with the same covariance structure of the cell under test, is available. We resort to a design procedure based upon the generalized likelihood ratio test (GLRT): first we derive the GLRT assuming that the textures are known, then we plug into the derived test suitable estimates of these parameters. Remarkably, the newly proposed detector has the constant false alarm rate (CFAR) property with respect to the texture statistical characterization. Moreover, even though it does not ensure the CFAR property with respect to the clutter covariance matrix, a sensitivity analysis shows that the probability of false alarm is only slightly affected by variations in the clutter correlation properties. Finally, the performance assessment, conducted via Monte Carlo simulations, confirms the capability of the receiver to operate in real radar scenarios.
{"title":"A polarimetric adaptive detector in non-Gaussian noise","authors":"A. De Maio, G. Alfano","doi":"10.1109/NRC.2002.999763","DOIUrl":"https://doi.org/10.1109/NRC.2002.999763","url":null,"abstract":"We address polarimetric adaptive detection of targets embedded in compound-Gaussian clutter with unknown covariance matrix. To this end we assume that a set of secondary data, free of signal components and with the same covariance structure of the cell under test, is available. We resort to a design procedure based upon the generalized likelihood ratio test (GLRT): first we derive the GLRT assuming that the textures are known, then we plug into the derived test suitable estimates of these parameters. Remarkably, the newly proposed detector has the constant false alarm rate (CFAR) property with respect to the texture statistical characterization. Moreover, even though it does not ensure the CFAR property with respect to the clutter covariance matrix, a sensitivity analysis shows that the probability of false alarm is only slightly affected by variations in the clutter correlation properties. Finally, the performance assessment, conducted via Monte Carlo simulations, confirms the capability of the receiver to operate in real radar scenarios.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"511 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132520379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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