Abstract:
A method and system for processing received sonar signals. The method and system generate bearing data signals based on the received sonar signal. The method and system continuously determine the signal strength of the received sonar signal and also continuously determine the total noise from the received sonar signal in the ocean environment in which the target is located. The method and system provide a sensor gain in response to the determined total noise and the signal strength, and adaptively calculate filter coefficients from the sensor gain and the determined total noise. The method and system also filter the generated bearing data signals using a filter having the calculated filter coefficients.

Description:
STATEMENT OF GOVERNMENT INTEREST 
     The invention described herein may be manufactured and used by or for the Government of the United States of America for governmental purposes without the payment of any royalties thereon or therefor. 
    
    
     BACKGROUND OF THE INVENTION 
     (1) Field of the Invention 
     The present invention generally relates to an adaptive passive sonar signal processing method and system. 
     (2) Description of the Prior Art 
     Sonar signal processing systems are known in the art. Edelblute et al. U.S. Pat. No. 4,754,282 discloses a data analysis system which uses an Eckart filter that has weights that are updated in accordance with a beam formed output. However, this system does not consider the environmental factors existing in an ocean environment in which a target is located. Zurek et al. U.S. Pat. No. 4,956,867 discloses an adaptive noise canceling apparatus in which adaptive filtering is inhibited in certain circumstances. Dragoset, Jr. U.S. Pat. No. 5,448,531 discloses a method for adaptively creating a filter capable of removing coherent environment noise from a seismic recording. O&#39;Brien, Jr. et al. U.S. Pat. No. 5,537,368 discloses an adaptive statistical filter system updated using data representative of sensed target motion and noise. Wynn U.S. Pat. No. 6,313,738 discloses an adaptive noise cancellation system that adaptively updates the weights of the system&#39;s adaptive filters based upon an input signal. 
     Other prior art systems utilize Eckart filters whose coefficients are obtained using pre-defined spectral levels of the noise and target. However, sonar systems utilizing such Eckart filters typically detect signals and generate bearing, range, speed, aspect and depth information that has less than desirable performance, e.g., reliability and accuracy. 
     None of these aforementioned patents disclose the technique of using a filter having adaptively calculated coefficients that are based upon the power spectrum of the target and the total noise in the ocean environment in which the target is located. 
     SUMMARY OF THE INVENTION 
     It is therefore an object of the present invention to provide a sonar signal processing method and system that utilizes a filter that filters beamformed data based on received sonar signals emanating from a target or source in an ocean environment. 
     It is another object of the present invention to provide a sonar system that adaptively calculates filter coefficients that depend upon the gain of a sonar sensor array that receives the sonar signals. 
     Yet another object of the present invention is to provide a sonar system that system that adaptively calculates filter coefficients that depend upon the total noise in the ocean environment in which the target is located. 
     Thus, the present invention is directed to a method and system for processing received sonar signals. The method and system generate bearing data signals based on the received sonar signal. The method and system continuously determine the signal strength of the received sonar signal and also continuously determine the total noise from the received sonar signal in the ocean environment in which the target is located. The method and system provide a sensor gain in response to the determined total noise and the signal strength, and adaptively calculate filter coefficients from the sensor gain and the determined total noise. The method and system also filter the generated bearing data signals using a filter having the calculated filter coefficients. In one embodiment, an Eckart filter is used to filter the generated bearing data signals. 
     Additional objects, features, aspects and advantages of the present invention are apparent from the drawings and specification which follow. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The features of the invention are believed to be novel and the elements characteristic of the invention are set forth with particularity in the appended claims. The figures are for illustration purposes only and are not drawn to scale. The invention itself, however, both as to organization and method of operation, may best be understood by reference to the detailed description which follows taken in conjunction with the accompanying drawings in which: 
     FIG. 1 is a block diagram of the adaptive sonar signal processing system in accordance with one embodiment of the present invention; and 
     FIG. 2 is a block diagram of the adaptive sonar signal processing system in accordance with another embodiment of the present invention. 
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENT 
     In describing the preferred embodiments of the present invention, reference will be made herein to FIGS. 1-2 of the drawings in which like numerals refer to like features of the invention. 
     Referring to FIG. 1, there is shown a block diagram of the adaptive sonar signal processing system of the present invention. The system shown in FIG. 1 is configured as an open-loop sonar signal processing system. Sensor  10  receives acoustic signals emanating from an object or target in an ocean environment. The received acoustic signals have a signal strength that depends upon several factors that are discussed in the ensuing description. In a preferred embodiment, sensor  10  has a variable gain. In one embodiment, sensor  10  comprises an array of acoustic transducers. Sensor  10  outputs sensed acoustic signals  12  for input into beamforming processor  14 . Beamforming processor  14  receives and processes sensed acoustic signals  12  received from sensor  10  and generates selected bearing signal  15  which defines the target bearing. Sensor  10  and beamforming processor  14  are well known in the art and, therefore, are not discussed in detail. 
     Selected bearing signal  15  is inputted into filter  16 . In accordance with the present invention, filter  16  has variable coefficients that are adaptively calculated in response to the gain of sensor  10  and the total noise in the ocean environment in which the target is located. Filter  16  outputs filtered target bearing signal  17 . In one embodiment, filter  16  is configured as an Eckart filter. For purposes of example, the ensuing description is in terms of filter  16  being configured as an Eckart filter. However, it is to be understood that an Eckart filter is just one example and that other types of filters can be used as well. The manner in which the filter coefficients of Eckart filter  16  are calculated is described in detail in the ensuing description. 
     Filtered target bearing signal  17  is inputted into sonar signal processor  18  which processes signal  17  and outputs data signal  19  which defines the bearing, range, depth, speed and aspect of the object. Sonar signal processor  18  is configured to implement various signal processing functions and algorithms such as analog-to-digital conversion, Fourier transforms and analysis, averaging, etc. which are known in the art. Data signal  19  is inputted into display device  20  which displays the bearing, range, depth, speed and aspect of the object in a predetermined format. Data signal  19  can also be provided to other peripheral devices (not shown) such as data storage systems, combat fire control systems, weapon control systems, etc. 
     Filter coefficient generation module  24  adaptively calculates coefficients for Eckart filter  16  in response to the gain of sensor  10  and the total noise in the ocean environment in which the target is located. 
     Data input interface  25  allows a user or sonar operator to input data signals that are processed by self noise processor  26  and environment model processor  28 . The sonar operator inputs data into data input interface  25  which defines the speed of the ship or vessel which is towing sensor  10 . This speed is referred to as “ownship” speed. Data input interface  25  outputs the ownship speed data as data signal  29 . Data signal  29  is input into self-noise processor  26 . Self-noise processor  26  comprises a library which contains noise data corresponding to particular ships and various speeds of ships. In response to signal  29 , self-noise processor  26  outputs data signal  30  which represents the self-noise power spectrum associated with the ship towing sensor  10 . Signal  30  is inputted into noise power summing module  31 . 
     The sonar operator also inputs data into data input interface  25  that defines sea state/wind speed, time (i.e. night, day, season, etc.), location (i.e., geographical location), sound velocity profile, sensor depth, and shipping density. This data is outputted from data input interface  25  as a plurality of signals referred to by numeral  32 . Signals  32  are provided to environment model processor  28 . The sonar operator also uses data input interface  25  to input hypothesized target bearing, range, depth, speed, aspect, and type data corresponding to the target. Data input interface  25  outputs the hypothesized target bearing, range, and depth data as target positioning signal  34  and the hypothesized target speed and aspect data signal  35 . Signal  34  is provided to environment model processor  28 . Processor  28  processes signals  32  and  34  and outputs ambient noise data signal  36  and a channel propagation loss data signal  38 . Ambient noise data signal  36  is inputted into noise power summing module  31  and is summed with the self-noise power defined by data signal  30  to produce a total noise power spectrum signal  40 . Signal  40  is inputted into filter coefficient generation module  24 . 
     Target speed and aspect signal  35  is inputted into target data processor  42 . Target data processor  42  comprises a library or data base that has information stored therein which is used to process signal  35 . Such information includes target signature recognition data that is associated with a plurality of possible target types, speeds and aspects. Target data processor  42  outputs a target power spectrum signal  43  that represents the power spectrum of the target. The channel loss propagation signal  38  and power spectrum signal  43  are provided to attenuation processor  44 . Attenuation processor  44  processes these signals  38  and  43  and generates attenuation signal  48  which represents the amount of attenuation sustained by the acoustic signals as they travel from sensor  12  to beamforming processors  14 . Attenuation signal  48  is inputted into sensor gain adjustment module  46 . Sensor gain adjustment module  46  processes attenuation signal  48  and generates a sensor gain signal  50 . The gain of the sensor compensates for channel propagation loss. Sensor gain signal  50  is inputted into filter coefficient generation module  24 . Although not shown in FIG. 1, it is to be understood that sensor gain signal  50  is also routed to sensor  10  in order to adjust the sensor gain appropriately. 
     Filter coefficient generation module  24  adaptively calculates coefficients for the Eckart filter based on the total noise defined by total noise power spectrum signal  40  and sensor gain signal  50  and outputs updated filter coefficient signal  52 . Since the data defined by total noise power spectrum signal  40  and sensor gain signal  50  is updated over time as a result of new or updated data being inputted into environment model processor  28  and target data processor  42  via data input interface  25 , the coefficients for the Eckart filter are continually and automatically adjusted thereby resulting in significantly more accurate filter coefficients. As a result, sonar signal processor  18  outputs relatively more reliable and accurate data pertaining to target bearing, depth, range, speed, and aspect. Thus, the open-loop feature of the system shown in FIG. 1 exhibits operating characteristics that provide for relatively improved detection functions in comparison to prior art systems. Such improved reliability and accuracy provides for optimum detection of a particular target at a particular range and depth. Furthermore, the overall processing time for producing the target bearing, depth, range, speed and aspect data is decreased. Additionally, the relatively high efficiency and accuracy of the processing function of the adaptive sonar signal processing system of the present invention allows relatively smaller sensor arrays to be utilized thereby reducing costs. 
     Referring to FIG. 2, there is shown another embodiment of the adaptive sonar signal processing system of the present invention. The embodiment shown in FIG. 2 is a closed-loop adaptive sonar signal processing system. In this embodiment, the sonar operator does not input hypothesized target bearing, range and depth into data input interface  25 . Thus, target positioning signal  34  is not utilized and therefore is not shown in FIG.  2 . Furthermore, the sonar operator does not input hypothesized target speed and aspect data. As a result, target aspect signal  35  only contains target type information. Sonar signal processor  18  outputs two additional signals  100  and  102 . A calculated target position signal  100  defines the target bearing, range and depth data and is fed back to environment model processor  28 . A calculated target aspect signal  102  represents target speed and aspect data and is fed back to target data processor  42 . Thus, environment model processor  28  processes bearing, range and depth data based on received acoustic signals instead of hypothesized data. Similarly, target data processor  42  processes target speed and aspect data based on received acoustic signals instead of hypothesized data. Since the data defined by signals  40  and  50  is constantly being updated as a result of the feedback feature of the system shown in FIG. 2, the coefficients of Eckart filter  16  are constantly and automatically updated. Thus, the closed-loop system of FIG. 2 exhibits operating characteristics that provide for relatively improved tracking functions in comparison to prior art systems. 
     The signal processors of the adaptive sonar signal processing system of the present invention can be implemented with commercially available signal processing hardware and software. Sensor gain adjustment device  46  as well as sonar display device  20  are known in the art and can be realized by suitable commercially available devices. 
     The method and system of the present invention can be applied to other types of acoustic signals (i.e. other than underwater acoustic signals) and electromagnetic signals used in communication systems. 
     The principals, preferred embodiments and modes of operation of the present invention have been described in the foregoing specification. The invention which is intended to be protected herein should not, however, be construed as limited to the particular forms disclosed, as these are to be regarded as illustrative rather than restrictive. Variations in changes may be made by those skilled in the art without departing from the spirit of the invention. Accordingly, the foregoing detailed description should be considered exemplary in nature and not limited to the scope and spirit of the invention as set forth in the attached claims.