43 results about "Generalised likelihood ratio test" patented technology

A method and system realize reliable wireless communications in non-coherent multiple-input multiple-output (MIMO) doubly-selective channels. The method uses Grassmannian space-time-frequency block codes and an iterative generalized likelihood ratio test (GLRT) with a multi-dimensional basis expansion model (BEM), decision reordering, and a fixed number of surviving candidates. The computational complexity of a non-coherent MIMO equalizer becomes linear as a function of a code length and a size of a modulation alphabet. The codebook, the alphabet size, the bit labeling, and the block power are optimized using worst-case channel statistics or instantaneous channel states. The method can use soft-information feedback from error correction codes, such as low-density-parity-check codes to improve performance.

An approach to determine cantilever movement is presented. An observer based state estimation and statistical signal detection and estimation techniques are applied to Atomic Force Microscopes. A first mode approximation model of the cantilever is considered and a Kalman filter is designed to estimate the dynamic states. The tip-sample interaction is modeled as an impulsive force applied to the cantilever in order to detect the presence of sample. A generalized likelihood ratio test is performed to obtain the decision rule and the maximum likelihood estimation of the unknown arrival time of the sample profile and unknown magnitude of it. The use of the transient data results in sample detection at least ten times faster than using the steady state characteristics.

An approach to determine cantilever movement is presented. An observer based state estimation and statistical signal detection and estimation techniques are applied to Atomic Force Microscopes. A first mode approximation model of the cantilever is considered and an observer is designed to estimate the dynamic states. The cantilever-sample interaction is modeled as an impulsive force applied to the cantilever in order to detect the presence of sample. A generalized likelihood ratio test is performed to obtain the decision rule and the maximum likelihood estimation of the unknown arrival time of the sample profile and unknown magnitude of it. The use of the transient data results in sample detection at least ten times faster than using the steady state characteristics.

A method provides space-time adaptive processing (STAP) for target detection using adaptive matched filters (AMF). A generalized likelihood ratio test (GLRT) is determined where spatial and temporal correlation matrices Q and A are assumed. Then, the correlation matrices A and Q are replaced with maximum likelihood (ML) estimates obtained only from training signals subject to a persymmetric constraint.

The invention discloses a simulation method of MIMO (Multiple Input Multiple Output) radar target detection under non-Gaussian clutter environment. The method comprises the following steps of: establishing a target detection model based on the auxiliary data which is close to a detected unit and does not contain the target; substituting a likelihood function with a detection signal to get the detection statistic; under a condition that a non-Gaussian clutter covariance matrix is known, obtaining a theoretical MIMO radar target detector by using a generalized likelihood ratio test theory. Under a condition that the non-Gaussian clutter covariance matrix is unknown, an appropriate clutter covariance matrix is estimated based on the auxiliary data, and the generalized likelihood ratio is substituted by the estimated clutter covariance matrix, thus, a MIMO radar adaptive detector is proposed.

The invention discloses a self-adaptive millimeter wave beam layered search method. The method comprises the following steps: 1, assuming a beam search scene and modeling a multi-layer beam codebook; 2, modeling a beam hierarchical search pilot signal; 3, laying self-adaptive wave beams into any layer, and using a generalized likelihood ratio for checking and judging whether the signal-to-noise ratio of the received pilot signals reaches a target value or not; if the target value is reached or the wave beam search time of the layer reaches a preset maximum value, stopping the search of the layer; otherwise, continuing the layer search; 4, searching any layer except the last layer in a layered manner, and selecting the to-be-searched angle space of the next layer after the single-layer search stopping condition in the step 3 is met; and 5, after the search of the last layer is stopped, selecting a final beam direction. According to the method, the beam search time can be automatically adjusted to ensure the beam search accuracy under the condition that the path loss and the SNR are unknown, the search time is automatically prolonged to ensure the search precision under the condition of low SNR, and the search time is reduced and the system overhead is reduced under the condition of high SNR.

The invention discloses a wireless microwave dew intensity monitoring method based on wet antenna cause discrimination. The method comprises the following steps: monitoring wireless microwave signal attenuation intensity; deducing dry period and wet period by using a Markov transformation model; using a generalized likelihood ratio test method to detect whether there is a wet antenna phenomenon caused by dew in the dry period; if the wet antenna phenomenon is detected, applying a trained ICA algorithm to separate out attenuation signals caused by a wet antenna from microwave signal attenuationintensity data received by the wireless microwave receiver; and establishing a model relationship between the attenuation value caused by the wet antenna and the dew intensity by using a Fresnel reflection formula to realize monitoring of the dew intensity. According to the method, a direct monitoring method and an indirect model method are combined, high-resolution monitoring of the dew intensity is achieved, a traditional dew monitoring method is innovated, meanwhile, an existing high-temporal-spatial-resolution microwave communication network is effectively utilized, manpower and materialresources are saved, and the monitoring precision of the dew intensity is improved.

The invention discloses a broadband radar target adaptive fusion detection method based on a skew-symmetry structure, belonging to the field of radar signal processing. Aiming at a broadband radar system for which auxiliary data is missing and a space symmetric linear array or a fixed coherent pulse recurrence interval is used, clutter background statistical characteristics are estimated through clutter covariance matrix skew-symmetry structured information in main data and the auxiliary data, target scattering point energy in all to-be-detected distance units is fused based on a one-step process generalized likelihood ratio detection criterion, the clutter information in the main data and the auxiliary data is used maximally, a broadband target skew-symmetry structured adaptive detector is designed, false alarm probability and detection probability analytical expression of the detector are derived, mathematical tool support is provided for detector threshold value setting and detection performance theoretical analysis, range spread target adaptive detection performance under an environment where the auxiliary data is missing is improved, and the method has a popularization and application value.