Abstract:
A system for rejecting wind noise at a plurality of sensors includes input logic, a processor and output logic. The input logic receives a signal from each of the plurality of sensors. The processor assigns a weight value to each of the received signals. The output logic derives a wind noise rejected output signal based on a function of the assigned weight values and the received signals.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     The instant application claims priority from provisional application No. 60/301,104, filed Jun. 26, 2001, and provisional application No. 60/306,624, filed Jul. 19, 2001, the disclosures of which are incorporated by reference herein in their entirety. 
     The instant application is related to co-pending Application No. 60/306,624, entitled “Systems and Methods for Adaptive Noise Cancellation” and filed on a same date herewith, the disclosure of which is incorporated by reference herein. 
    
    
     FIELD OF THE INVENTION 
     The present invention relates generally to systems and methods for acoustic detection and, more particularly, to systems and methods for rejecting wind noise in acoustic detection systems. 
     BACKGROUND OF THE INVENTION 
     A number of conventional systems detect, classify, and track air and ground bodies or targets. The sensing elements that permit these systems to perform these functions are typically arrays of microphones whose outputs are processed to reject coherent interfering acoustic noise sources (such as nearby machinery). Other sources of system noise include general acoustic background noise (e.g., leaf rustling) and wind noise. Both of these sources are uncorrelated between microphones. They can, however, be of sufficient magnitude to significantly impact system performance. 
     While uncorrelated noise is addressed by spatial array processing, there are limits to signal-to-noise improvements that can be achieved, usually on the order of 10*log N, where N is the number of microphones. Since ambient acoustic noise is scenario dependent, it can only be minimized by finding the quietest array location. At low wind speeds, system performance will be limited by ambient acoustic noise. However, at some wind speed, wind noise will become the dominant noise source—for typical scenarios, at approximately 5 mph at low frequencies. The primary source of wind noise is the fluctuating, non-acoustic pressure due to the turbulent boundary layer induced by the presence of the sensor in the wind flow field. The impact of an increase in wind noise is a reduction in all aspects of system performance: detection range, probability of correct classification, and bearing estimation. For example, detection range can be reduced by a factor of two for each 3-6 dB increase in wind noise (depending on acoustic propagation conditions). 
     Therefore, there exists a need for systems and methods that can reduce wind noise so as to improve the performance of acoustic detection systems such as, for example, acoustic detection systems employed in vehicle mounted systems for which the effective wind speed includes the relative velocity of the vehicle when the vehicle is in motion. 
     SUMMARY OF THE INVENTION 
     Systems and methods consistent with the present invention address this and other needs by providing a multi-sensor windscreen assembly, and associated wind noise rejection circuitry, to enable the detection of a desired acoustic signal while maximizing rejection of wind noise. Multiple sensors, consistent with the present invention, may be distributed across a surface of a three dimensional body, such as a sphere, cylinder, or cone. Adaptive weights may be applied to the signal output from each of the multiple sensors so as to pass low wind noise signals and reject those with high wind noise. Signals from sensors subjected to high levels of unsteady pressures due to wind turbulence may be given low weights and, thus, substantially rejected, while signals from sensors not subjected to these flow disturbances may be given large weights and, thus, substantially passed. The values of the adaptive weights may be continuously, or periodically, updated in order to account for wind direction and speed changes at the multi-sensor windscreen assembly. Systems and methods consistent with the present invention, thus, provide an adaptive windscreen system that can reject wind noise and, thereby, improve the measurement and detection of desired acoustic signals. 
     In accordance with the purpose of the invention as embodied and broadly described herein, a method of rejecting wind noise includes distributing a plurality of acoustic sensors over a surface of a body; identifying at least one sensor of the plurality of acoustic sensors that is subject to low wind noise; passing signals from the at least one identified sensor as low wind noise signals; and rejecting signals from non-identified sensors of the plurality of acoustic sensors as high wind noise signals. 
     In another implementation consistent with the present invention, a method of rejecting signal noise includes receiving signals from a plurality of sensors and assigning a weight value to each of the received signals. The method further includes deriving a noise rejected output signal based on a function of the assigned weight values and the received signals. 
     In a further implementation consistent with the present invention, a windscreen includes a three dimensional body mounted on a first surface, the body configured to rotate with respect to the first surface and comprising at least one second surface. The windscreen further includes a plurality of sensors distributed on the at least one second surface of the body, the sensors configured to sense forces acting upon the body. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and, together with the description, explain the invention. In the drawings, 
         FIG. 1  illustrates an exemplary multi-sensor assembly consistent with the present invention; 
         FIG. 2  illustrates an exemplary multi-sensor assembly with a spherical windscreen and equatorially distributed sensors consistent with the present invention; 
         FIG. 3  illustrates exemplary components of a noise rejection unit consistent with the present invention; and 
         FIG. 4  is a flowchart that illustrates an exemplary process for wind noise rejection consistent with the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     The following detailed description of the invention refers to the accompanying drawings. The same reference numbers in different drawings may identify the same or similar elements. Also, the following detailed description does not limit the invention. Instead, the scope of the invention is defined by the appended claims. 
     Systems and methods, consistent with the present invention, provide mechanisms that adaptively reject noise in multiple signals received from a multi-sensor device. A processor of the present invention assigns a weight parameter to each signal of the multiple signals. Each assigned weight parameter may correspond to a noise level of the associated sensor signal. Output circuitry may derive a noise rejected output signal based on a function of the assigned weight parameters and the received signals. In some embodiments, for example, the output circuitry may include multiplier elements and a summer. In this case, the noise rejected output signal may include a summation of the products of each assigned weight parameter with its respective sensor signal. 
     Exemplary Multi-Senor-Assembly 
       FIG. 1  illustrates an exemplary multi-sensor assembly  100  consistent with the present invention. Multi-sensor assembly  100  may include a windscreen  105  coupled to a support structure  110 . As illustrated, windscreen  105  may be configured as a three dimensional sphere. Windscreen  105  may, alternatively, be configured as a three dimensional cylinder, cone or other shape (not shown). Windscreen  105  may further be constructed of a rigid, semi-rigid, or solid material. Windscreen  105  may also be constructed of a permeable or non-permeable material. For example, windscreen  105  may be constructed of foam and, thus, would be semi-rigid and permeable to fluids such as air or water. As an additional example, windscreen  105  may be constructed of a solid material such as plastic or the like that would be non-permeable to fluids and rigid. 
     As shown in  FIG. 1 , multiple sensors (sensor  1   115 - 1  through sensor N  115 -N) may be distributed on a surface of windscreen  105 . As further illustrated in  FIG. 2 , the multiple sensors  115  may be distributed around an equator of spherical windscreen  105 . One skilled in the art will recognize, also, that other sensor distributions may be possible. For example, sensors  115  may be distributed at icosahedral points (not shown) on the surface of spherical windscreen  105 . Distribution of the sensors across a surface of windscreen  105  can depend on the shape of the windscreen (e.g., spherical, cylindrical, conical) and the particular air-flow anticipated upon the windscreen. 
     Each of the multiple sensors  115  may include any type of conventional transducer for measuring force of pressure. A piezoelectric transducer (e.g., a microphone) is one example of such a conventional transducer. In some embodiments of the present invention, each of the multiple sensors  115  may measure acoustic and non-acoustic air pressure. 
     Exemplary Wind Noise Rejection Unit 
       FIG. 3  illustrates an exemplary unit  300  in which systems and methods, consistent with the present invention, may be implemented for rejecting wind noise sensed at a multi-sensor device, such as multi-sensor assembly  100 . Wind rejection unit  300  may include multiple input buffers  305 , a weight update processor  310 , multiple multipliers  315 , and a summer  320 . The weights {w 1 , w 2 , . . . , w N } supplied by weight update processor may be frequency dependent, and thus  FIG. 3  represents one frequency “slice” of the entire frequency spectrum. A bank of units  300  may be implemented, for example, in hardware or software, to cover the entire desired frequency band. Input buffers  305  may receive signals from each sensor  115  of multi-sensor assembly  100  and pass the signals to multipliers  315  and weight update processor  310 . Weight update processor  310  may receive each signal {S 1 , S 2 , . . . , S N } from multi-sensor assembly  105  and, according to a process, such as the exemplary process described with respect to  FIG. 4  below, may provide weights to each of the multiplier elements  315  based on each received signal. Multiplier elements  315  may multiply each of the provided weights with a corresponding sensor signal. 
     The weighted signals {w 1 S 1 , w 2 S 2 , . . . , w N S N } from multiplier elements  315  may be summed at summer  320 . The summed weighted signals (w 1 S 1 +w 2 S 2 + . . . +w N S N ) can be output from wind rejection unit  300  as a noise rejected output signal  325 . This noise-reduced output signal  325  may be used in a conventional acoustic detection system (not shown) for detecting, classifying, and tracking objects or targets. 
     Exemplary Wind Noise Refection Process 
       FIG. 4  illustrates an exemplary process, consistent with the present invention, for rejecting wind noise contained in signals {S 1 , S 2 , . . . , S N } received from multiple sensors. The exemplary process may begin by determining a vector w of optimal minimum variance weights that can be applied to the received sensor signals {S 1 , S 2 , . . . , S N } [act  400 ]. Weight vector w can be determined using the following equation:
   w=[W   1   w   2    . . . w   N ] T   =R   −1 /1 R   −1 1  Eqn. (1) 
where
         R is the covariance matrix of the sensor signals over the current frequency “slice,” and   1 is the vector of N ones.
 
R can be determined according to the following equation:
 
 R=E{SS   T }  Eqn. (2)
 
where E is the expected value, and
 
 S=[S   1   S   2    . . . S   N ] T .
 
Weight update processor  310  may, for example, determine the optimal minimum variance weights represented by weight vector w. The optimal minimum variance weight vector w may pass low wind noise sensor signals and may reject high wind noise sensor signals. Signals from sensors subjected to high levels of unsteady pressures due to turbulence and wake flow may, thus, be rejected by unit  300 , while signals from sensors located a distance away from the flow disturbances may be given large weight values. The formulation represented by Eqns. (1) and (2) may be appropriate for a sensor array whose maximum dimension is small compared with the signal wavelength of interest. Those skilled in the art will recognize that many variants and modifications to this optimal weight calculation, and the time-varying estimation of the covariance matrix, R, may exist and may be used in the present invention.
       
     The sensor signals {S 1 , S 2 , . . . , S N } may then each be multiplied by their corresponding weight {w 1 , w 2 , . . . , w N } of weight vector w [act  405 ]. For example, a corresponding multiplier element  315  can multiply each sensor signal by a respective assigned weight. The weighted sensor signals {w 1 S 1 , w 2 S 2 , . . . , w N S N } may then be summed to produce a noise rejected output signal  325  (w 1 S 1 +w 2 S 2 + . . . +w N S N ) [act  410 ]. Summer  320  of wind rejection unit  300  may, for example, sum each of the weighted sensor signals. The noise-reduced output signal  325  may, for example, be used in a conventional acoustic detection system for detecting, classifying, and/or tracking objects or targets. 
     Conclusion 
     Systems and methods, consistent with the present invention, provide mechanisms that enable the detection of a desired acoustic signal incident at a multi-sensor windscreen assembly while maximizing rejection of wind noise. The multi-sensor windscreen assembly may include multiple sensors distributed across a surface of a three dimensional windscreen, such as a sphere, cylinder, or cone. Noise rejection circuitry may apply adaptive weights to the signal output from each of the sensors so as to pass low wind noise signals and reject high wind noise signals. Signals from sensors subjected to high levels of unsteady pressures due to wind turbulence and wake flow will be given low weights and, thus, substantially rejected, while signals from sensors not subjected to these flow disturbances will be given large weights and, thus, substantially passed. The values of the adaptive weights may be continuously, or periodically, updated in order to account for wind direction and speed changes at the multi-sensor windscreen assembly. 
     The foregoing description of exemplary embodiments of the present invention provides illustration and description, but is not intended to be exhaustive or to limit the invention to the precise form disclosed. Modifications and variations are possible in light of the above teachings or may be acquired from practice of the invention. For example, while certain components of the invention have been described as implemented in hardware and others in software, other configurations may be possible. Furthermore, while the use of weights has been described above as one exemplary method for selecting the sensor signals to be used to compose noise rejected output signal, mechanical rotation of windscreen  105  may provide the mechanism for selecting the sensor signals that are to compose the noise rejected output signal. In such an embodiment, windscreen  105  may be rotated and the signals of the sensors facing into the wind may be used for composing the noise rejected output signal, while signals from sensors facing away from the wind would not be used. In some exemplary embodiments, windscreen  105  may include a streamlined body with fins attached at the rear, thus, permitting windscreen  105  to rotate in the manner of a weathervane. 
     Also, while series of acts have been described with regard to  FIG. 4 , the order of the acts may be altered in other implementations. No element, step, or instruction used in the description of the present application should be construed as critical or essential to the invention unless explicity described as such. The scope of the invention is defined by the following claims and their equivalents.